DOCTORAL DEGREE IN AGRI-FOOD TECHNOLOGY AND BIOTECHNOLOGY

• CHE MUSTAPA, MUHAMMAD ADZRAN: Consumer Preferences and Acceptance for Sustainable Food Systems
  
  Author: CHE MUSTAPA, MUHAMMAD ADZRAN
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN AGRI-FOOD TECHNOLOGY AND BIOTECHNOLOGY
  Department: Department of Agri-Food Engineering and Biotechnology (DEAB)
  Mode: Article-based thesis
  Deposit date: 18/06/2025
  Reading date: 25/09/2025
  Reading time: 11:00
  Reading place: Sala de Graus de l'EEABB, Campus del Baix Llobregat-UPC, C. Esteve Terradas 8, Castelldefels // I en sessió pública al meet.google.com/sph-anam-gqv
  Thesis director: KALLAS CALOT, ZEIN
  Thesis abstract: As consumers increasingly recognise the health, ethical, and environmental impacts of their dietary choices, a shift toward sustainable food systems is emerging. This dissertation explores consumer preferences, willingness to pay (WTP), and factors influencing the acceptance of innovative and sustainable food products through seven empirical studies.The first study examines Spanish consumers’ willingness to consume (WTC) animal products fed with insects. A survey of 1,260 individuals analysed using Kruskal–Wallis and Mann–Whitney U tests reveals significant uncertainty, with females showing greater acceptance. Key factors influencing WTC include financial situation, age, and education.The second study explores the effect of informational contexts on WTP for insect-fed animal products using a Heckman model with 1,006 responses. Findings indicate WTP premiums of 21%–31%, with higher education, online shopping habits, and shopping at municipal markets increasing WTC likelihood.The third study assesses WTP for organic aquaculture products, focusing on organic sea bass. A survey of 1,300 consumers analysed via binary logistic regression finds a €2.26 (25%) WTP premium. Age, financial stability, and attributes like price, origin, and freshness significantly influence WTP.The fourth study examines Spanish consumers’ sensory acceptance of plant-based products. Data from 132 respondents analysed using SPSS and PLS-SEM show that perceived behavioural control, sensory perceptions, attitudes, and informed tasting significantly impact purchasing intentions.The fifth study investigates acceptance and WTP for legume-based gnocchi using the Becker–DeGroot–Marschak (BDM) auction method. A hedonic evaluation of 127 consumers reveals moderate attitudes toward legume-based products. Tasting negatively impacts WTP, while education, income, government support perceptions, and sensory attributes influence WTP.The sixth study analyses European meat substitute consumption patterns using Mintel data from 5,000 consumers across four countries. Over half have reduced red meat intake, with Germans showing the highest vegan adherence. Women consume less meat and are more inclined to reduce intake. Economic and sustainability concerns drive reduction, with preferences for locally sourced, natural, and meat-like substitutes.The seventh study conducts a meta-analysis of consumer WTP for short food supply chain (SFSC) products across 47 studies. Findings indicate an average 34.5% premium, with gender, education, study year, age, region, product category, and sustainability attributes affecting WTP. Organic products receive the highest WTP, with meat, poultry, dairy, and honey leading categories.
  

DOCTORAL DEGREE IN ARCHITECTURAL DESIGN

• ALVAREZ BEAUMONT GRAYEB, LORENA DENISSE: Alvar Aalto. Maison Louis Carré. Del concepto a la obra: Procesos compositivos e influencias culturales
  
  Author: ALVAREZ BEAUMONT GRAYEB, LORENA DENISSE
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ARCHITECTURAL DESIGN
  Department: Department of Architectural Design (PA)
  Mode: Normal
  Deposit date: 14/07/2025
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: SAUQUET LLONCH, ROGER JOAN | LINARES SOLER, ALFREDO
  Thesis abstract: Alvar Aalto was one of the most important architects of the 20th century and a key figure in the history of design. He was part of the so-called Modern Movement and is considered one of the great masters of architecture from that period. Although much of his work has been extensively studied, the Maison Louis Carré has received less attention due to its private nature until 2007. Built between 1957 and 1959 in Bazoches-sur-Guyonne (Yvelines), near Paris, the house was designed for Louis Carré, a renowned French art dealer and collector of modern art. Given the limited availability of both specific and general published sources on the subject, this study aims to contribute new insights into the Maison Louis Carré and Alvar Aalto's architecture.The information presented in this research has been 'constructed' primarily through the collection of period documents, site visits, and interviews with individuals connected to the building. Its objective is to analyze the underlying process behind the design and construction of the house by identifying the architectural strategies employed by Aalto.The study first offers an overview of the historical, social, artistic, and architectural context of Aalto’s time, as well as earlier influences. It also examines the impact of various architectural traditions—particularly from Finland, Greece, Italy, and Japan—whose presence is evident in specific formal and conceptual elements of the house, suggesting potential sources of inspiration from these cultures.The second part of the study focuses on the influence of the client-architect relationship, which played a crucial role in shaping the architectural program and design decisions. It also considers the significant involvement of the Aaltos and Louis Carré in the realization of the building, a project of high logistical complexity that would have been unfeasible without the sustained commitment of all three parties. Similarly, the analysis explores the Finnish and Nordic elements integrated by Aalto into the design, thoughtfully adapted to the client’s lifestyle, as well as to French culture and landscape—resulting in a coherent synthesis between both cultural contexts.The final section presents a more technical analysis of the design process developed by the architect—from the initial site visit to the completion of the work—covering aspects such as design strategies, environmental considerations, functionality, materiality, and structural systems, with the goal of offering a comprehensive view of the making of the Maison Louis Carré.This building occupies a special place in Alvar Aalto’s body of work, not only because it is set in a new context like France, but also because—beyond its aesthetics and timeless quality—it belongs to a period when the architect had already reached a high level of professional maturity. This is evident in his design approach and in how he engages with the landscape, incorporating a range of innovative construction techniques. These techniques manage to reflect the culture and interpretations of their time while endowing the work with a distinct language that remains evocative, dynamic, and of exceptional quality and originality even today.But what can we learn from Alvar Aalto today? In what ways could contemporary architecture achieve the level of quality and originality so clearly embodied in the timeless beauty of this house? Addressing these questions and demonstrating how the conceptual, compositional, and aesthetic values embedded in the Maison Louis Carré could still enrich contemporary architectural practice—when reinterpreted in light of current technological and productive capacities—is what drives the development of this research.
  
• BACH, ANNA KAARINA: Alison & Peter Smithson, Axel Bruchhäuser and the Hexenhaus. The added value of the conglomerate ordering
  
  Author: BACH, ANNA KAARINA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ARCHITECTURAL DESIGN
  Department: Department of Architectural Design (PA)
  Mode: Normal
  Deposit date: 11/07/2025
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: MÀRIA SERRANO, MARIA MAGDALENA
  Thesis abstract: Between 1985 and 2002, British architects Alison and Peter Smithson transformed the Hexenhaus—a modest half-timbered building in Bad Karlshafen, Germany—into one of the late twentieth century's most remarkable houses. Through additions, extractions, satellite buildings, furnishing operations, and alternative routes, they redefined the relationship between the house and its landscape. This process fostered a close relationship with their client, Axel Bruchhäuser, who still resides in the house.This research provides a detailed study of the design and construction process of the Hexenhaus, using new graphic materials to illustrate its chronological evolution. The thesis examines 22 distinct interventions, considering them as both individual elements and parts of the overall project. It offers insights into an important but lesser-known period in the Smithsons' careers, spanning from the late 1970s until their deaths (Alison in 1993 and Peter in 2003). The Hexenhaus encapsulates the Smithsons' recurring themes of territory and fabric, place-response, internal project logic, and the ephemeral versus the permanent. The Hexenhaus architecture is examined within the context of the Smithsons' broader work and unique project conditions, marked by an extended design process that transcended the conventional architect-client relationship. The thesis focuses on the Hexenhaus, learning from its unique conditions and strategies, and shedding light on an obscure period of the Smithsons' professional journey. The house is interpreted through the concept of Conglomerate Ordering, linking its form to the Smithsons' mature ideas and observations.Two preliminary visits in 2013 and 2015 and the further research trips to the house and the Tecta Archive in 2018, 2019, and 2023 provided essential first-hand and archival information. Reorganising Hexenhaus documents at the Tecta Archive in 2018 offered a crucial overview of materials, such as plans, sketches, meeting minutes, notes, letters, and postcards, which became the focus of close study. The graphic material produced by the Smithsons and their correspondence with Axel Bruchhäuser illustrate their close intellectual relationship and reveal the design process's intricacies.The direct examination of the Hexenhaus yielded direct information, including precise measurements, photographs, and audio-recorded interviews with Axel Bruchhäuser. The thesis views the Hexenhaus as a collection of micro-architectures and objects forming a living, evolving organism. Consequently, the research extends beyond the house to include a detailed inventory of its furniture and miscellanea that play a crucial role in the architectural experience and design process of the Hexenhaus.The thesis exemplifies an accumulative architecture that responds to pre-existence, embracing the 'as found' as a situation to learn from and contribute to. The time embedded in the process allows architecture to be tested, adjusted, and corrected throughout an extended development, positioning Hexenhaus as an open-ended conclusion to Alison and Peter Smithson’s life’s work.
  
• DE LA FUENTE GONZÁLEZ, FÉLIX: Arquitectura Comparada
  
  Author: DE LA FUENTE GONZÁLEZ, FÉLIX
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ARCHITECTURAL DESIGN
  Department: Department of Architectural Design (PA)
  Mode: Normal
  Deposit date: 11/07/2025
  Reading date: 02/09/2025
  Reading time: 11:00
  Reading place: ETSAB (Esc. Técnica Sup. Arquitectura de Bcn)-Pl Baja-Sala GradosAv. Diagonal, 649-651-BCN(MEET: https://meet.google.com/fva-tfab-tgu; 10:30 h)
  Thesis director: MÀRIA SERRANO, MARIA MAGDALENA | MONTEYS ROIG, FCO JAVIER
  Thesis abstract: —I— Architecture is a way of ordering the pieces of the world according to their reciprocal affinities, and this involves comparing. Because the word “architecture”, as well as referring to how buildings, cities, territory and objects find their form and technical intelligence according to what is human in them, also refers to another, perhaps more elementary notion: that an architecture is a meaningful order between things, an associative and deliberate order, an order based on the bond provided by the intimate affinities between things. Discovering these affinities, constructing them and judging them entails placing them in a comparative space where they become legible in between the pieces, in their interdistances. In this way we often become aware of unsuspected arguments between images, which we would find difficult to appreciate in their individual quality, without relation, without architecture.—II— Comparative Architecture is a field of knowledge based on three foundations. The first is a specific methodology, the critical comparative method, with a dual facet of analysis and hermeneutics, and with a transversal approach based on the affinities between things. In Comparative Architecture the method is king and prior to the themes, since its incisive application on collected objects will be what “activates” their relationships and makes arguments emerge according to relative positions and distances. The second foundation is its object of study, which are the forms and concepts of material culture: those of buildings, objects, territory, cities and landscape, and also the pure forms of technology... forms, in short, projected by man according to his knowledge and sensibility. Finally, the third foundation of Comparative Architecture is that its design is constructed with two critical devices: the comparative montage and the comparative essay, both equally intentional and representative as analysis, either in visual language or in the language of words.—III— Comparative Architecture is aligned with the spirit of many of those comparative sciences that were sprouting throughout the 19th century in very diverse fields of knowledge, as an authentic “culture of comparison”: Comparative Anatomy, Comparative Physiology, Comparative Linguistics, Comparative Mythology, Comparative Geology, Comparative Literature, etc. All of them shared a genuine outlook that involved adopting the critical comparative method as a constructive principle and the space of affinities as a space for thought and research. But if there was one thing that these comparative sciences had in common, it was the ability to take advantage of an environment of widespread accessibility and abundance of study material, starting from the handling of copious collections in an effort to critically order their pieces to unravel their reciprocal attributes, their invariances and transversalities.—IV— Today, images of material culture are presented to us in social networks and web publications in such a degree of hyper-accessibility and hyper-abundance that it would seem that the nineteenth-century condition of the fragmentary and unconnected has now reached an ultimate limit state in perpetual crisis. Insofar as the sciences of comparison encourage knowledge among the dislocated and disconnected, Comparative Architecture seems especially attuned to this hypermodern condition of our times, to offer us a critical incentive with which to handle ourselves in the profusion, simultaneity and synchronicity of publications and social networks. This thesis presents Comparative Architecture in a self-contained way, as a recognisable field of knowledge with an unprecedented potential for development thanks to the contemporary image, reproduced digitally. The thesis is composed of a homonymous volume dedicated to theoretical concerns, and an annex entitled “the coupled and the multiple” dedicated to the practical facet of comparing.
  

DOCTORAL DEGREE IN ARTIFICIAL INTELLIGENCE

• GUTIÉRREZ MONDRAGÓN, MARIO ALBERTO: Exploring the Dynamics of the beta2-Adrenergic Receptor: Insights from Explainable AI in GPCR Research
  
  Author: GUTIÉRREZ MONDRAGÓN, MARIO ALBERTO
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ARTIFICIAL INTELLIGENCE
  Department: Department of Computer Science (CS)
  Mode: Normal
  Deposit date: 12/05/2025
  Reading date: 16/09/2025
  Reading time: 11:00
  Reading place: FIB Sala d'actes Manuel Martí Recober B6-planta 0
  Thesis director: VELLIDO ALCACENA, ALFREDO | KÖNIG, CAROLINE LEONORE
  Thesis abstract: G-protein coupled receptors are transmembrane proteins that serve as critical mediators between extracellular signals and intracellular responses. These highly dynamic entities orchestrate a wide array of cellular processes in response to various stimuli, including hormones, neurotransmitters, and environmental signals. Due to their versatility and central role in cellular communication, GPCRs are prime pharmacological targets for treating a wide spectrum of diseases, ranging from diabetes and Alzheimer's to various forms of cancer. Despite significant advances in understanding their dynamic conformational landscapes, the precise molecular mechanisms underlying their transient and intricate shifts, especially upon ligand binding, remain obscured by the complexity of their structures. This poses substantial challenges to the elucidation of the processes that govern their signaling mechanisms. In this thesis, we leverage the wealth of information generated by Molecular Dynamics simulations through advanced Machine Learning models to help decode the complex conformational landscape of GPCRs. A crucial step in our approach involves transforming the raw MD data into structured formats that are more suitable for analysis. Deep Neural Networks, known for their strength in capturing intricate relationships within large datasets, form the backbone of the thesis. When coupled with state-of-the-art explainability techniques, these models not only produce accurate classifications, but also reveal molecular mechanisms that drive the behavior of GPCRs.Our goal extends beyond building reliable models for classification. We aim to reveal critical patterns and insights that deepen our understanding of GPCR dynamics. By focusing on the beta2 -adrenergic receptor, our aim is to improve the interpretation of receptor behavior while creating a reliable framework for broader applications in proteomics.
  

DOCTORAL DEGREE IN BUSINESS ADMINISTRATION AND MANAGEMENT

• SAVALL MAÑO, MARIA: Towards a more sustainable B2C delivery in Barcelona: bridging consumer, parcel carrier, and municipal perspectives
  
  Author: SAVALL MAÑO, MARIA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN BUSINESS ADMINISTRATION AND MANAGEMENT
  Department: Department of Management (OE)
  Mode: Normal
  Deposit date: 15/07/2025
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: RIBAS VILA, IMMACULADA
  Thesis abstract: The rapid growth of e-commerce is worsening the negative effects of urban distribution on cities. Although the last-mile segment comprises only a small part of the supply chain, its impact is disproportionately high in terms of noise, congestion, emissions, and public space use. As online shopping expands, the distribution model has remained largely unchanged, with companies simply adding more delivery vehicles to meet demand. This vehicle increase intensifies negative urban impacts, and Barcelona is no exception.Given the significant social, environmental, and economic consequences of the current urban distribution model for online purchases, exploring and implementing alternative approaches is essential. This requires considering the perspectives of all stakeholders involved in or influencing urban e-commerce distribution: consumers, parcel carriers, and municipalities. Understanding these perspectives helps identify the actions each group must take to transition toward more sustainable distribution models. This thesis proposes and analyses sustainable B2C distribution solutions for Barcelona by bridging these three perspectives, aiming to reduce noise, congestion, and pollution while improving public spaces.First, the perspective of consumers is examined. The literature highlights that e-commerce consumer behaviour is highly location-dependent; thus, a dedicated survey is conducted among Barcelona consumers. Analysis revealed four distinct consumer clusters: occasional male shoppers, who shop online once or less per month and prefer home delivery; frequent male shoppers, who shop more than three times per month and also favour home delivery; regular female shoppers, who shop once or twice per month and tend to use collection points; and occasional female shoppers, who shop online once or less per month and also prefer home delivery. To encourage greener delivery choices, increasing home delivery costs may influence occasional shoppers, while alternative strategies are needed for frequent male shoppers.Second, the perspective of parcel carriers is analysed. The literature suggests that Out-of-Home Delivery (OOHD) options and Urban Consolidation Centres (UCCs) support more sustainable distribution. Based on the characteristics of parcel carriers in Barcelona, a methodology is designed to identify optimal locations for these infrastructures and quantify associated transport and environmental costs. Implementing OOHD and UCCs in Barcelona is evaluated across various carrier types and scenarios. Results show both strategies reduce costs, with the greatest benefits observed when transhipment spaces and trolleys are used by high- and medium-volume carriers. For low-volume carriers, delivering 50% of parcels to collection points offers greater savings than using transhipment spaces.Third, the municipal government’s perspective is considered. The literature identifies designated loading and unloading time windows and road pricing strategies as possible regulatory tools to reduce freight distribution impacts. These measures are adapted to Barcelona’s context. Simulations show that avoiding peak hours with time windows significantly reduces economic impacts. To further reduce B2C externalities, introducing a strategic, variable fee for L/U area use proves even more effective.Through its methodologies and results, this thesis demonstrates the potential to reduce the impact of B2C distribution in Barcelona. Moreover, the findings offer a valuable resource not only for local authorities and parcel carriers seeking to lower economic and environmental costs but also for other cities facing similar challenges.
  

DOCTORAL DEGREE IN CHEMICAL PROCESS ENGINEERING

• LU, XUAN: Metal-Decorated Ceria-Based Reducible Oxide Catalysts for CO2 Transformation
  
  Author: LU, XUAN
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN CHEMICAL PROCESS ENGINEERING
  Department: Department of Chemical Engineering (EQ)
  Mode: Normal
  Deposit date: 16/07/2025
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: LLORCA PIQUE, JORDI | CABOT CODINA, ANDREU
  Thesis abstract: Noble metal clusters and single atoms have been considered as effective co-catalysts for the enhancement of carbon dioxide hydrogenation due to their singular geometric structures, electronic properties and unique reactivity. Nevertheless, the design of a low-cost and easy synthesis procedure for ultrasmall metal species is an urgent yet challenging task. In this thesis, we have synthesized CeO2-based catalysts decorated with non-noble metals (Cu and Ni) and bimetallic clusters (Cu-Ga) through hydrothermal and mechanochemical processes for CO2 transformation. In Chapter 3, bimetallic clusters (Cu-Ga) loaded on Ce0.9Zr0.1O2 are synthesized and characterized, and their catalytic performance for methanol production was investigated. By maintaining a constant total amount of Cu and Ga while varying the Cu/Ga ratio, we demonstrate that modifying the support surface with an optimal Cu/Ga ratio enhances CO2 adsorption and activation. This improvement stems from the compensatory generation of H2 dissociation at Ga sites, which directly interact with oxygen vacancies-a critical factor in the catalytic process.In Chapter 4, CeO2 exposing preferentially {001}, {110} and {111} facets are prepared and loaded with Ni monometallic clusters to investigate their unique catalytic properties for CO2 methanation. Experimental characterization reveals that Ni supported on CeO2 nanorods exposing {110} and {111} facets exhibited the highest activity.In Chapter 5, I analyze the effect of different highly-dispersed copper on CeO2 for the reverse water-gas shift reaction (RWGS). I systematically examine both the copper loading amount and the preparation method (ball milling versus conventional incipient wetness impregnation), observing significant differences in catalytic activity. To elucidate the enhanced Cu-CeO2 interaction induced by ball milling, I conduct comprehensive characterization (XRD, XPS, N2O Titration and in situ DRIFT et. al) studies to determine copper speciation at varying dispersion levels and to clarify the reaction mechanism. In Chapter 6, the effect of the introduction of Ga to Cu/CeO2 for thermostability during the RWGS reaction is studied. To improve the stability of Cu/CeO2 catalysts, a strategy through Ga incorporation is developed, achieving an optimal balance between activity and stability for the RWGS reaction. It is also observed that Ga doping in the CeO2 support effectively suppresses Cu aggregation during reduction treatments by modulating both CeO2 reducibility and electron transfer from CeO2 to Cu.
  

DOCTORAL DEGREE IN CIVIL ENGINEERING

• BAL, PRADEEP KUMAR: Mathematical and computational modeling of the active mechanics of multicellular systems: from cell-cell adhesion to epithelial reshaping
  
  Author: BAL, PRADEEP KUMAR
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN CIVIL ENGINEERING
  Department: Barcelona School of Civil Engineering (ETSECCPB)
  Mode: Normal
  Deposit date: 30/06/2025
  Reading date: 18/09/2025
  Reading time: 10:30
  Reading place: Sala Zienkiewich (CIMNE) Building C1, UPC - Campus North Gran Capitan S/N 08034 Barcelona
  Thesis director: ARROYO BALAGUER, MARINO
  Thesis abstract: This thesis develops theoretical and computational frameworks to model two fundamental mechanical functions of multicellular tissues: cell-cell adhesion and epithelial reshaping. These processes are controlled by sub-cellular dynamics, yet they manifest at mesoscopic scales, posing a challenge for existing models. The work is structured in two parts, each addressing a different aspect of tissue mechanics while sharing a common approach based on irreversible thermodynamics and active gel theory.In Part I, the focus is on modeling the dynamic formation and organization of cell-cell adhesions, particularly between pairs of cells. A mesoscale theoretical model is developed that couples the mechanics of the cellular surface, chemical kinetics of adhesion molecules, their lateral diffusion on the membrane, and feedback with the actomyosin cortex. The framework relies on Onsager's variational formalism to ensure thermodynamic consistency and is implemented computationally in both axisymmetric and 3D finite element formulations. Simulations reveal how mechano-chemical couplings (including the reduction of cortical contractility within adhesions, force-induced bond activation, and immobilization of activated bonds) drive the self-organization of mature adhesion patches. This work not only reproduces experimental observations of adhesion behavior but also sets the stage for future modeling of adhesion turnover, decohesion dynamics, and asymmetrical cell contacts.Part II focuses on epithelial reshaping, a key driver of morphogenesis. We propose a continuum shell theory for epithelial monolayers derived from sub-cellular descriptions of the actin cortex as an active gel. Two formulations are introduced: a Kirchhoff shell theory with perpendicular lateral junctions, and a more general Cosserat theory that allows for junctional tilt. These models are implemented numerically using finite element methods and validated against 3D vertex simulations. Applications include the study of apico-basal asymmetries, buckling, and wrinkling in epithelial tissues, particularly under rapid deflation as in recent experimental setups. The continuum model demonstrates how cortical viscoelasticity, viscous drag by the surrounding medium, and curvature anisotropy determine the morphology and patterning of wrinkles in epithelial shells. Future directions include accounting for evolving junctional networks and for biochemical signaling.Together, these contributions offer a mesoscale framework to bridge sub-cellular dynamics with tissue-scale mechanical behavior, providing mechanistic insight into processes central to tissue development, integrity, and morphogenesis
  

DOCTORAL DEGREE IN COMPUTER ARCHITECTURE

• DE HARO RUIZ, JUAN MIGUEL: Accelerating many-core, heterogeneous, and distributed architectures with hardware runtimes and programming models
  
  Author: DE HARO RUIZ, JUAN MIGUEL
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN COMPUTER ARCHITECTURE
  Department: Department of Computer Architecture (DAC)
  Mode: Normal
  Deposit date: 10/07/2025
  Reading date: 10/09/2025
  Reading time: 12:00
  Reading place: C6-E106
  Thesis director: ALVAREZ MARTINEZ, CARLOS | JIMENEZ GONZALEZ, DANIEL
  Thesis abstract: Due to increasing concern about energy efficiency and the current trend to scale out HPC systems to many computing nodes, this thesis tries to tackle both problems with the help of hardware acceleration and programming models.Regarding the first topic, FPGAs have been the target of study due to their high flexibility to adapt to any computing workload and due to their high energy efficiency. We present extensions to the OmpSs@FPGA framework, which provides a high-level task-based programming interface to non-FPGA experts.These extensions include compiler directives to automatically optimize FPGA code, a hardware task scheduling runtime with dependence analysis called POM, and a multi-FPGA MPI-like API and runtime, called OMPIF.In addition, we present the Implicit Message Passing (IMP) model, which combines task-based and message-passing programming models, leveraging dependence information and a static data distribution.IMP automatically communicates data between nodes when required by the data dependencies of a task.Therefore, the user does not need to write any call to MPI or OMPIF in the code, as this is handled by IMP.We evaluate this model on both FPGA and CPU clusters, with hardware acceleration for task scheduling and message passing using the POM and OMPIF runtimes.For CPU clusters, we study several ways to incorporate POM into an SoC, first with an embedded FPGA, then we design it as an ASIC for a RISC-V core, and finally in an FPGA softcore also based on RISC-V.In the last case, we use both POM and OMPIF to evaluate distributed applications with a cluster of FPGAs that emulate a CPU cluster.We evaluate IMP and regular MPI+tasks programming with several benchmarks: Matrix Multiply, Spectra, N-body, Heat, and Cholesky.With the mentioned contributions, we achieve several objectives.First, we demonstrate that with OmpSs@FPGA we can achieve similar absolute performance to a CPU node for some benchmarks, like N-body, and outperform in energy efficiency to similar CPU and GPU architectures (in area and technology).Second, we also evaluate multi-FPGA applications on three different clusters: cloudFPGA, ESSPER, and MEEP, which have very distinct characteristics.With IMP, we show that we can scale linearly the N-body, Heat, and Cholesky benchmarks to 64 FPGAs.For CPUs, we are also able to scale linearly with the same benchmarks on an 8-core, 64-node cluster, with 512 cores in total.With our hardware-software co-design, which combines the hardware acceleration of task scheduling and message passing with IMP, we show a solution to accelerate HPC workloads as transparently as possible to the programmer, thus boosting productivity.This solution has been designed for heterogeneous systems based on FPGAs, but also based on CPUs.The latter also benefit significantly from the runtime overhead reduction thanks to the hardware acceleration.
  

DOCTORAL DEGREE IN COMPUTING

• QUISHPI BETÚN, LUIS HERNÁN: Generación de Modelos de Procesos y Decisiones a partir de Documentos de Texto
  
  Author: QUISHPI BETÚN, LUIS HERNÁN
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN COMPUTING
  Department: Department of Computer Science (CS)
  Mode: Normal
  Deposit date: 13/06/2025
  Reading date: 08/09/2025
  Reading time: 10:00
  Reading place: FIB Sala d'actes Manuel Martí Recober, B6-planta 0
  Thesis director: CARMONA VARGAS, JOSE | PADRO CIRERA, LLUIS
  Thesis abstract: This thesis addresses the importance of formal models for the efficient management of business processes (BPM) and business decision management (BDM) in a constantly evolving corporate environment. Within the BPM context, the relevance of Business Process Model and Notation (BPMN) is emphasized as a standardized modeling language for the coherent and comprehensible representation of business processes. Similarly, in BDM, the utility of Decision Model and Notation (DMN) is highlighted for the standardization of decision modeling and documentation in organizations.This research identifies a common challenge in organizations: the reliance on documents in various formats, including textual descriptions in natural language, for process and decision documentation. These documents pose difficulties due to the ambiguity of natural language and their unstructured nature, leading to significant time investment in their interpretation and the need for specialized personnel to convert them into formal models such as BPMN and DMN.The main contribution of this dissertation is the proposal of an innovative solution through the development of an automated technique for extracting and generating formal BPMN and DMN models from textual documents. Two distinct methodological approaches are presented:* A traditional Natural Language Processing (NLP) approach, leveraging structured patterns based on syntactic trees (Tree-based patterns), which enables the precise extraction of key textual fragments (such as activities, conditions, and decisions) and their transformation into formal models like BPMN and DMN.* A Large Language Models (LLM)-based approach that employs advanced language processing techniques and deep learning capabilities to interpret textual descriptions in natural language and transform them into formal representations such as BPMN and DMN. Through strategically designed prompt instructions, this approach guides the extraction of processes and decisions, enabling a more flexible and adaptable generation of formal models without relying on rigid syntactic rules.Both approaches aim to address the limitations of traditional methodologies by reducing the cognitive load on modelers, minimizing human intervention in the conversion of text into formal models, and enabling the automated integration of these models into business process management systems (BPMS).The focus of this thesis is not merely on reviewing and understanding existing models but on proposing substantial and practical improvements based on experience in generating formal models in real business environments. Strategies for generating graphical representations of processes and decisions (e.g., BPMN, DMN) are explored.This doctoral thesis seeks to make a significant contribution to the field of business process and decision management by combining established BPMN and DMN theory with practical approaches and innovative solutions. The automatic generation of these models will not only provide a clearer representation of processes but will also enhance organizations' ability to make efficient decisions in a dynamic and competitive business environment.Keywords: Business Process Management, Business Decision Management, BPMN, DMN, Natural Language Processing, NLP, Large Language Models, LLM, Tree-based Patterns, Process Mining
  

DOCTORAL DEGREE IN ENVIRONMENTAL ENGINEERING

• GONZÁLEZ CURBELO, MIGUEL ÁNGEL: Plastic Pollution in Marine Ecosystems: Spatiotemporal Assessment in Beach Sediments of Protected Coastal Areas
  
  Author: GONZÁLEZ CURBELO, MIGUEL ÁNGEL
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ENVIRONMENTAL ENGINEERING
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 15/05/2025
  Reading date: 04/09/2025
  Reading time: 10:00
  Reading place: Sala de actos del Intexter. Edificio TR-7.Campus de Terrassa.Carrer de Colom, 15, 08222 Terrassa, Barcelona
  Thesis director:
  Thesis abstract: Plastic pollution has emerged as a critical threat to marine ecosystems, particularly in ecologically sensitive and protected coastal areas. This doctoral thesis presents a spatiotemporal assessment of plastic particle debris, including microplastics, in beach sediments from marine protected areas (MPAs) on the Caribbean coast of La Guajira, Colombia, and marine Special Areas of Conservation (SACs) in Tenerife, Canary Islands, Spain. Fieldwork involved systematic sampling across 13 beaches (seven in La Guajira and six in Tenerife), representing a variety of environmental conditions. The study in La Guajira, the first of its kind in the region, revealed microplastic abundance ranging from 2.4 ± 0.6 to 22 ± 7 microplastics/m2, with concentrations varying statistically by beach use but not significantly between the two sampling periods. Filaments, primarily from fishing activities, were the most prevalent type (38.5%). In Tenerife´s marine SACs, a comprehensive 12-week assessment of macro-, meso-, and microplastics uncovered significant spatial and temporal variability. Playa de Montaña Roja emerged as a notable pollution hotspot, with 64 ± 36 mesoplastics/m2 and 506 ± 364 microplastics/m2. Fragments dominated the samples (80%), especially white and light-colored, indicating their likely origin as secondary particles from consumer products. In both scenarios, the most common polymers detected were polyethylene (PE), polypropylene (PP), and polystyrene, due to their buoyancy in marine environments, which also reflects global trends in production. Further analysis of heavy metal presence in microplastics from Tenerife´s SACs, using microwave-assisted acid digestion and inductively coupled plasma mass spectrometry, identified sixteen elements, including appreciable levels of six Environmental Protection Agency (EPA)-priority heavy metals: chromium, nickel, copper, zinc, cadmium, and lead. Comparative analysis showed a preferential accumulation of chromium, copper, lead, and cadmium in PE fragments over PP pellets, highlighting the role of polymer type. Cadmium concentration was particularly high (105 ± 15 mg/kg) in PE fragments from Playa de Montaña Roja SAC. In summary, this doctoral thesis provides robust empirical evidence on the abundance, spatiotemporal distribution, and characteristics (shape, color, and polymer type) of microplastics in MPAs, along with associated heavy metal concentrations. The findings presented herein not only reinforce the urgency of addressing plastic pollution but also offer practical tools and insights to guide the development of public policies aimed at protecting vulnerable marine ecosystems from microplastic-related threats.
  
• RUALES DÁVILA, EVELYN ALICIA: Biogas and Bio-Based Products Recovery from Microalgae: A Biorefinery Approach
  
  Author: RUALES DÁVILA, EVELYN ALICIA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ENVIRONMENTAL ENGINEERING
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 03/07/2025
  Reading date: 26/09/2025
  Reading time: 10:30
  Reading place: Place: ETSECCPB UPC, Campus Nord Building A3. Classroom: Aula Master C/Jordi Girona, 1-3 08034 B arcelona
  Thesis director: FERRER MARTI, IVET | GARFI, MARIANNA
  Thesis abstract: Microalgal biomass has attracted significant interest due its potential to produce valuable bio-based products and biofuels, owing to its rapid growth, high photosynthetic efficiency, and adaptability to diverse environmental conditions. However, challenges such as enhancing productivity, achieving cost-effective processing, and maximising biomass utilisation persist in this field. This PhD thesis aimed to develop an integrated microalgal biorefinery approach for the sustainable valorisation of microalgal biomass, focusing on the recovery of valuable bio-based products and biogas through anaerobic digestion (AD) of extracted microalgal biomass. Three studies were conducted, each representing different microalgal biorefinery scenarios, to evaluate the performance of these biorefinery approaches in a circular bioeconomy model. The first study assessed the dual recovery of biostimulants and biogas from Scenedesmus sp. cultivated in an outdoor demonstrative high-rate algal pond (HRAP) using freshwater and recycled nutrient media. The biostimulant extracts improved seed germination, root and shoot growth, and chlorophyll retention in watercress, mung beans, cucumbers, and wheat. The potential for biogas production from harvested biomass (Raw) and biostimulant-extracted biomass (Stim-E) was evaluated using mesophilic biochemical methane potential (BMP) tests. AD of Stim-E increased methane yield by 20% (293 mL CH₄/ g VS), and improved the kinetics by 10% compared to Raw biomass. The second study expanded upon this approach by treating wastewater with a Scenedesmus-bacterial consortium cultivated in a demonstrative HRAP to treat urban wastewater. Harvested biomass was processed to extract biostimulants, which maintained their plant growth-promoting properties. Downstream processing functioned as a pretreatment, preserving 91% of the methane yield from Raw biomass (276 mL CH4/g VS). Co-digestion with primary sludge (PS) enhanced methane yield and kinetics by 24% and 43%, respectively, compared to Raw biomass. Additionally, the fate of contaminants of emerging concern (CECs) was analysed to evaluate their mitigation during microalgae-based wastewater treatment and bioproduct recovery. Over 80% of the analysed CECs were removed during the wastewater treatment, and the low residual CECs in the biostimulant extracts confirmed their environmental safety for agricultural applications. These results demonstrated the successful integration of resource recovery within microalgae-based wastewater treatment processes and their alignment with circular bioeconomy principles. The third study focused on carotenoid and biogas recovery from Scenedesmus sp. cultivated in HRAPs treating urban wastewater. Carotenoid extraction yielded up to 4.3 mg/g total suspended solids (TSS), with lutein identified as the predominant pigment. AD of carotenoid-extracted biomass (CEB) retained 86% of the methane yield from Raw biomass, while co-digestion with PS increased yields by 44-86%. These findings demonstrate the potential of a cascading microalgal biorefinery model that integrates the extraction of valuable products with bioenergy generation to enhance resource efficiency and waste valorisation. This thesis demonstrates the versatility of microalgae in three interconnected domains: AD, extraction of valuable products, and wastewater treatment. This study provides insights into scalable strategies for integrated microalgal biorefineries, offering sustainable solutions to energy and environmental challenges. The outcomes highlight synergies across biorefinery processes and lay a foundation for future research aimed at enhancing technical performance, reducing environmental impacts, and improving economic viability within circular bioeconomy frameworks.
  
• SAZDOVSKI, ILIJA: Relativity of time, circularity and recycled material quality in LCA for fast-moving products
  
  Author: SAZDOVSKI, ILIJA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ENVIRONMENTAL ENGINEERING
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Article-based thesis
  Deposit date: 14/07/2025
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: FULLANA PALMER, PERE
  Thesis abstract: Life Cycle Assessment (LCA) is the preferred methodology for quantifying the environmental impact of systems along value chains. The LCA’s most important methodological feature is the use of the Functional Unit (FU) and focusing on the services that the system delivers.Circular Economy (CEc) has more recently proposed overarching principles to move towards sustainability. This new concept is introduced to overcome the limitations of the traditional linear economy model.The Product Environmental Footprint (PEF) is a common LCA science-based methodology developed by the European Commission. It aims at making LCA more suitable for comparing products.PEF’s most important methodological feature is the Circular Footprint Formula (CFF). CFF offers circularity-driven insights and defines a method to allocate emissions and avoided emissions of use and recycling materials and energy between upstream and downstream production systems, as well to include the influence of the materials' quality.A growing body of scientific literature aims at providing adequate metrics to improve the comparison between the two economic paradigms (linear vs circular), or among systems serving the same function primarily through LCA. To develop more comprehensive LCA research, by the principles of the circular economy, the definitions of the FU need to be changed by including multiple-loop recycling of the materials. Firstly, this Ph.D. thesis aims to improve the framework for usage of LCA methodology by involving circularity principles for fast-moving goods, through the involvement of additional variables such as time.The proposed theoretical contribution is focused on packaging, which is a special case of fast-moving products. The proposed method can be replicated for all other fast-moving goods circulating in the technical cycles. The need to include the time variable is particularly obvious for fast-moving goods, such as packaging. The introduction of time as a variable offered a possibility for the development of circularity indicators using mathematical representation and the development of a formula for production of an “n+1” product. Involving time in LCA exposes the slow recycling process of the secondary materials, extended shelf-life, and some methodological circumstances, like the calculation of the biogenic carbon. These aspects are not covered if the environmental assessments only consider the life cycle perspective along the value chain and not along time. The importance of involving the time variable in environmental assessments is proven as well with the practical examples. Secondly, the thesis highlights the importance of accurate values for the quality of the material in multiple recycling, which prolongs the presence of the material in the technosphere.Our literature review showed that quality degradation has mostly been neglected. Understanding the quality changes of the material over time, together with knowledge of the number of loops a material can be recycled, is key to improving the assessments. A laboratory testing of the quality changes is conducted utilizing fossil-based and bio-based plastic materials in closed-loop recycling based on the “cradle to cradle principles”. The tests consider the mechanical, optical and processing changes, and the maximal recycling cycles that a material can undergo in the extrusion process.These test-based indicators of quality can be used by the PEF method as the maximal value for quality degradation at the point of substitution. The LCA practice has been changed previously. The oil crisis prompted the calculation of cumulative energy demand, while the climate crisis forced the development of the Global Warming Potential. Based on the problem of depletion of materials and the linear practices, the science needs to involve the circularity paradigm in environmental assessment studies.
  
• TUCI, FRANCESCA: Identification of Critical Issues and Development of Strategies to Increase the Environmental Sustainability of Textile Districts in Europe
  
  Author: TUCI, FRANCESCA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ENVIRONMENTAL ENGINEERING
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 11/07/2025
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: LOPEZ GRIMAU, VICTOR | GORI, RICCARDO
  Thesis abstract: The textile industry is highly water-intensive, consuming 200-400 liters of freshwater per kg of product, making it the EU's 3rd largest water consumer. The Textile BAT Reference document (TXT Bref) highlights the volume of water discharged and its chemical load as key environmental concerns applicable throughout the European Union, including Italy and Spain. This study examines water-related challenges in the textile districts of Prato (Italy) and Catalonia (Spain), aiming to develop strategies for enhanced sustainability through innovative wastewater management, resource recycling, and sludge treatment. TXT BAT conclusions introduced associated emission levels (BAT-AELs) for direct and indirect wastewater discharges. Consequently, textile companies characterized by indirect discharge will be supposed to respect the BAT-AELs of certain contaminants unless the downstream wastewater treatment plant (WWTP) can abate these contaminants. In this study, mass balance calculations of two WWTPs located in Prato were conducted to verify that the removal of specific pollutants primarily originating from textile processes resulted from an effective treatment process and not merely a dilution effect with domestic wastewater. The findings confirmed the effective removal of critical compounds like COD, BiAS, sulfides, phenols, and hydrocarbons. Contaminants like Zn, Cu, Ba, Crtot, and Sb showed >50% removal efficiency, though results varied with sampling procedures. TXT BAT conclusions promote reuse and recycling to reduce freshwater use and wastewater generation. Prato, home to Europe’s largest wastewater recycling plant, faces challenges with high hardness in reclaimed water from Baciacavallo WWTP. It was demonstrated that an ultrafiltration-nanofiltration (UF-NF) pilot plant can reduce water hardness by more than 98%, regardless of the operating conditions. Furthermore, a simplified steady-state model of the chloride cycle revealed that replacing ion-exchange resin technology, used in Prato for water softening, with a UF-NF system leads to a substantial reduction in chloride concentration, enabling the reuse of reclaimed wastewater for other purposes such as irrigation.This research demonstrated that NF can treat dyeing wastewater and reuse the permeate for the dyeing process, thereby avoiding freshwater consumption and recovering salts. To this end, a laboratory NF pilot plant was employed to treat and reuse wastewater from the dyeing of cotton with reactive dyes. Permeate reuse had no impact on the final product's color reproducibility and allowed saving up to 24% of NaCl and 32% of Na2CO3. Moreover, electrochemical oxidation was applied to treat the NF concentrate, resulting in a color degradation level exceeding 95%. This outcome suggests the potential for the reuse of the concentrate, accompanied by the recovery of additional resources. Textile sludge (TXS) disposal, mainly via landfilling or incineration, is an environmental challenge. Therefore, in this work, biochemical methane potential (BMP) tests were conducted on three types of sludge (i.e., municipal, textile, and mixed) to assess anaerobic digestion (AD) as a potential sustainable treatment alternative. The results demonstrated the feasibility and benefits of AD for the valorization of TXS, with co-digestion as a promising approach to maximize biogas production efficiency. Finally, the study addressed microplastic (MP) pollution, proposing a method to quantify and identify MPs in wastewater. Understanding WWTP efficiency in MP removal supports efforts to mitigate emerging environmental concerns. The study outlines strategies to improve the environmental sustainability of textile districts. By adopting technologies like NF and AD, industries could reduce resource use, enhance wastewater treatment, and recover byproducts. It also highlights the need to tackle issues like microplastics with advanced monitoring, promoting sustainable practices in the European textile sector.
  

DOCTORAL DEGREE IN GEOTECHNICAL ENGINEERING

• TORRA I TRUNCAL, ONA: A multitemporal and multiscale analysis of soil erosion and sediment transport. Application to the badlands in the Upper Llobregat River Basin.
  
  Author: TORRA I TRUNCAL, ONA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN GEOTECHNICAL ENGINEERING
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Article-based thesis
  Deposit date: 09/07/2025
  Reading date: 05/09/2025
  Reading time: 10:00
  Reading place: ETSECCPB. UPC, Campus Nord Building C1. Classroom: 002 C/Jordi Girona, 1-3 08034 Barcelona
  Thesis director: HURLIMANN ZIEGLER, MARCEL | PUIG POLO, CAROLINA
  Thesis abstract: Badlands are among the most active geomorphic environments on Earth, exhibiting extreme erosion rates, sparse vegetation, and steep, deeply dissected slopes. In mountainous Mediterranean regions, seasonal climate variability - characterized by winter freeze-thaw cycles and intense summer convective storms - amplifies sediment production and transport. This study investigates the drivers and dynamics of erosion in the Upper Llobregat River Basin (ULRB), a representative Mediterranean badland system in the southeastern Pyrenees. Using a multi-scale and multi-method approach that integrates TLS monitoring, UAV-based photogrammetry, physically-based modelling, and machine learning, we assess sediment dynamics at slope, catchment, and regional scales. Erosion rates at the slope scale ranged from 16500 T km−2 year−1 to 30000 T km−2 year−1. Sediment export at the catchment scale ranged from 42 to 105 T·km⁻²·year⁻¹ over the study period (2020–2024), averaging only 10.7% of the long-term annual yield of 880 T·km⁻²·year-1. Landscape Evolution Model (LEM) reproduced seasonal sediment cycles and highlighted the importance of hydrological connectivity and temporary sediment storage. At the regional scale, Random Forest models predicted badland susceptibility with high accuracy, although model generalizability declined outside the training domain. Additionally, shallow landslides also played a minor episodic role in sediment delivery during some intense, widespread rainstorms, although not directly linked to badland dynamics. The findings underscore the importance of integrating diverse methods and spatial scales to capture the complexity of badland erosion processes. The work also provides essential insights for erosion monitoring, land management, and sediment risk mitigation in sensitive Mediterranean mountain landscapes.
  

DOCTORAL DEGREE IN MARINE SCIENCES

• YILMAZ, ELIF: Interannual to decadal variability in the Southern Ocean surface CO2 fluxes in relation with the large-scale atmospheric modes.
  
  Author: YILMAZ, ELIF
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN MARINE SCIENCES
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 03/07/2025
  Reading date: 25/09/2025
  Reading time: 15:00
  Reading place: Place: ETSECCPB UPC, Campus Nord Building C2. Classroom: 212 C/Jordi Girona, 1-3 08034 Barcelona
  Thesis director: BERNARDELLO, RAFFAELE | MARTIN, ADRIAN PETER
  Thesis abstract: AbstractThe Southern Ocean (<35◦S), which encircles Antarctica, plays a disproportionately large role in the global carbon cycle, accounting for nearly half of the ocean’s uptake of anthropogenic CO₂. This critical function has helped mitigate the pace of atmospheric CO₂ accumulation and climate change. However, observations over recent decades have revealed substantial interannual to decadal variability in the Southern Ocean carbon sink, characterized by alternating periods of weakening and reinvigoration. Understanding the drivers of this variability is crucial for improving predictions of the ocean’s future carbon uptake capacity and its feedbacks on the climate system.This thesis investigates the atmospheric and oceanic processes underlying the variability of Southern Ocean CO₂ fluxes, with a focus on the influence of major climate modes including the Southern Annular Mode (SAM), the Pacific-South American (PSA) pattern, and Zonal Wave 3 (ZW3). Through a combination of reanalysis datasets, empirical orthogonal function and wavelet analyses, observation-based CO₂ flux products, and ocean-only numerical simulations, the thesis systematically diagnoses the mechanisms linking atmospheric variability to ocean carbon dynamics.The results identify SAM as the principal driver of CO₂ flux variability on seasonal to decadal timescales, modulating surface wind patterns, Ekman upwelling, and sea surface temperature (SST) anomalies that affect CO₂ exchange. ENSO and ZW3 are shown to exert important secondary effects, introducing regional asymmetries and modulating the physical and biological drivers of CO₂ fluxes, particularly in the Pacific sector. A novel finding is the detection of a delayed warming mechanism, whereby positive SAM phases enhance eddy kinetic energy, amplifying thermal effects on surface pCO₂ and partially offsetting the expected CO₂ uptake from weakened upwelling.The thesis also conducts a comprehensive evaluation of nine observation-based CO₂ products, highlighting uncertainties, mismatches, and shared patterns that improve our understanding of carbon cycle variability. Importantly, the results underscore the need to improve the representation of mesoscale processes, asymmetric climate modes, and atmosphere-ocean coupling in Earth system models to enhance their predictive capability.Overall, this research provides new insights into the drivers of Southern Ocean CO₂ variability, offering a framework to refine predictions of future carbon-climate feedbacks and to better anticipate the ocean’s role in mitigating anthropogenic climate change.
  

DOCTORAL DEGREE IN MATERIALS SCIENCE AND ENGINEERING

• SOUSA MACHADO, PEDRO VINÍCIUS: Computational Constitutive Modeling of WC-Co Hardmetals: From Small to Large Specimen Scale
  
  Author: SOUSA MACHADO, PEDRO VINÍCIUS
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN MATERIALS SCIENCE AND ENGINEERING
  Department: Department of Materials Science and Engineering (CEM)
  Mode: Article-based thesis
  Deposit date: 26/06/2025
  Reading date: 05/09/2025
  Reading time: 11:30
  Reading place: ESCOLA D'ENGINYERIA BARCELONA EST C/Eduard Maristany, 16 (08019 Barcelona) 934137400 Planta 0 Aula A A0.02 https://eebe.upc.edu/ca/lescola/com-arribar
  Thesis director: JIMENEZ PIQUÉ, EMILIO | CANER BASKURT, FERHUN CEM
  Thesis abstract: In this thesis, the mechanical behavior of tungsten carbide-cobalt (WC-Co) hardmetal, a multiphase composite, is thoroughly investigated through computational modeling techniques. First, the thesis focusses on the small-scale, where the constituent’s assemblage and constitution are not only clearly visible and discernible, but also play a major role in the mechanical behavior. Then, stochastic factors that affect small-scale specimens’ strength are accounted for. Finally, the thesis focuses on the large-scale, through the implementation of a model that connects small- and large-scale properties into a single framework.At the first stage of the work, data published on (1) nanoindentation on WC particles and the Co matrix; (2) tensile tests on nanowires (NWs) made of WC-Co hardmetals; and (3) compression tests on micropillars made of WC-Co hardmetals are used for the development of a numerical methodology. To do so, it is developed a novel computational framework that includes two distinct microplane constitutive models developed for the WC and Co phases separately. For the Co matrix, the microplane J2-plasticity model, called MPJ2, is developed, while for the WC particles, a modified version of the microplane model M7 is used, called M7WC. As for simulation meshes, a full realistic 3D representation is used, derived from experimental tomography reconstructions of two WC-Co hardmetal grades. After optimizing the parameters of MPJ2 and the M7WC models with experimental data, the finite element (FE) predictions not only confirm the extensive experimental observations but also provide further insights into the mechanical behavior of these composites.In the second stage of the thesis, significant uncertainties in the mechanical behavior of the WC-Co hardmetals at the small specimen level are addressed. They arise due to factors such as the intrinsic randomness of the microstructure and possible existence of defects. A stochastic finite element method (SFEM) is used in conjunction with the deterministic models, M7WC and MPJ2, by introducing controlled randomness to some of the parameters of these models. The meshes are sampled from an existing tomography of a WC-Co grade using LHS. The results effectively capture the strength distribution of these ceramic-metal composites at small-scale under tension.Finally, in the third part of the thesis, and aiming to demonstrate that at the large-scale the mechanical properties are also dependent on the microstructure, a new constitutive model for the FE modeling of WC-Co hardmetals at the large-scale is introduced, effectively serving as a multiscale approach. Known as the microplane model for hardmetals (MPHM), the model is calibrated using stress-strain test data obtained under uniaxial tension and compression from specimens with varying grain sizes and cobalt contents. Once calibrated, the model with fixed parameters is employed to predict additional experimental data from uniaxial tension, uniaxial compression, and four-point bending tests sourced from literature. The model demonstrates a high level of accuracy in predicting experimental data across a broad range of cobalt weight fractions (3 to 27 wt%) and WC grain sizes (0.35 to 1.85 μm). The model requires only four commonly available material constants as inputs: cobalt content, grain size, uniaxial compressive strength, and uniaxial tensile strength. Put simply, it is developed a model for large-scale behavior of a wide range of WC-Co grades where only easily measurable material properties are necessary as input parameters.
  

DOCTORAL DEGREE IN NATURAL RESOURCES AND THE ENVIRONMENT

• SAVADKOOHI, MARJAN: Evaluating harmonized equivalent black carbon mass concentration and source apportionment for air quality assessment
  
  Author: SAVADKOOHI, MARJAN
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN NATURAL RESOURCES AND THE ENVIRONMENT
  Department: Department of Mining, Industrial and ICT Engineering (EMIT)
  Mode: Article-based thesis
  Deposit date: 26/06/2025
  Reading date: 06/10/2025
  Reading time: 11:00
  Reading place: Sala Multimèdia B3 - Escola Tècnica Superior d'Enginyeria de Telecomunicació de Barcelona
  Thesis director: PANDOLFI, MARCO | ALASTUEY UROS, JOSE ANDRES
  Thesis abstract: Black carbon (BC), derived from optical absorption measurements, has emerged as an air quality (AQ) metric due to its significant effects on air quality, climate, and public health. As BC cannot be directly measured, inconsistencies arise in estimating its equivalent mass. The Europeans’ new AQ directive mandates BC monitoring at supersites and recommends it at hotspots, defining it as carbonaceous aerosols measured by light absorption. In atmospheric sciences, equivalent black carbon (eBC) is commonly defined as the mass concentration indirectly derived from measuring light attenuation by particles collected on filters at specific wavelengths (λ) using filter absorption photometers (FAPs). The measured attenuation is converted to absorption coefficient (babs), and then to eBC mass using predefined mass absorption cross-section (MAC), either default or calibrated with elemental carbon (EC). Despite regulatory progress, accurate eBC quantification and source apportionment remain challenging due to the absence of a standardized reference method and operational inconsistencies across monitoring networks. This thesis addresses these limitations by harmonizing absorption measurements, refining eBC estimation, and improving source apportionment methodologies. It further incorporates advanced computational tools to enhance consistency and interpretability in eBC reporting. Ambient eBC data from 50+ monitoring sites across Europe, including urban background (UB), traffic (TR), suburban (SUB), and regional background (RB) areas, were analyzed to study spatial and temporal variability. In the first phase, harmonized light absorption measurements and historical eBC data revealed a clear decreasing trend in eBC concentrations, TR > UB > SUB > RB, with a northward gradient consistent with other pollutants such as PM2.5. Strong seasonal variability was observed, with winter peaks at UB and SUB due to increased domestic heating and low atmospheric mixing. This methodology was also applied in harmonizing eBC observations across US regions, where emissions from gasoline and diesel vehicles were reduced, but wildfires increased regional eBC levels. eBC was apportioned into liquid fuel (eBCLF) and solid fuel (eBCSF) sources using Aethalometer (AE33) data and the common Aethalometer model. Despite its limitations, the method showed strong eBCLF dominance, while eBCSF retained regional relevance. A decreasing eBCLF trend was linked to reduced diesel emissions, whereas eBCSF remained stable or increased in some areas, suggesting persistent solid fuel use. To enhance eBC estimation, the second phase explored the spatial-temporal variability of site- and instrument-specific MACs using collocated EC and absorption data. Estimations based on nominal MACs overestimated eBC by up to 50%, whereas rolling site-specific MACs improved accuracy. A strong seasonal MAC dependence highlighted the need for continuous calibration. In the third phase, source apportionment was refined by deriving site-specific Absorption Ångström Exponent (AAE) values from AE33 data. A percentile-based method to estimate AAELF and AAESF (from summer and winter AAE distributions, respectively) was validated using chemical tracers (e.g., m/z 60 for biomass burning). Results showed that fixed AAE values were not universally applicable, reinforcing the need for site- and season-specific values to improve source characterization. Finally, integrating multi-wavelength optical and chemical datasets with multi-time resolution factor analysis improved the determination of site- and source-specific AAE. Machine learning models were also developed as virtual sensors for eBC estimation, showing strong cross-site transferability and offering a scalable solution for AQ monitoring. Overall, this thesis lays the foundation for a more standardized approach of eBC monitoring, supporting its inclusion as a regulated pollutant and reinforcing its role in AQ and climate policies.
  
• VERA BURAU, MARIA ALEJANDRA: Estrategias para una Extracción Sostenible en Minería de Superficie
  
  Author: VERA BURAU, MARIA ALEJANDRA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN NATURAL RESOURCES AND THE ENVIRONMENT
  Department: Department of Mining, Industrial and ICT Engineering (EMIT)
  Mode: Normal
  Deposit date: 05/06/2025
  Reading date: 10/09/2025
  Reading time: 16:00
  Reading place: Sala d'Actes Escola Politècnica Superior d'Enginyeria de Manresa
  Thesis director: SANMIQUEL PERA, LLUIS | BASCOMPTA MASSANÈS, MARC
  Thesis abstract: Mining is a fundamental sector for global economic development; however, it faces significant challenges related to the environmental impacts of its operations and the growing demand from stakeholders for sustainable and responsible practices. To ensure the long-term viability of the sector, it is essential to implement technical innovations and strategies that optimize costs, timelines, and productivity, while simultaneously integrating sustainability criteria from a holistic perspective.This study analyzes the incorporation of ESG (Environmental, Social, and Governance) criteria in the early stages of mining engineering, design, and planning, through the analysis of two surface mining case studies. In the first case, different economic and design scenarios are evaluated by integrating technical and economic parameters, comparing fleet models in terms of operating costs, production efficiency, fuel consumption, and CO₂ emissions. In the second case study, ESG criteria are integrated from the geological modeling phase through the inclusion of specific variables, combining technical, economic, and socio-environmental aspects such as energy consumption, emissions, and investment in human capital.The results of this research demonstrate that the early integration of ESG criteria into mine planning not only optimizes economic performance but also minimizes negative impacts on the environment and local communities. In this way, it promotes the development of mining projects that are economically viable, environmentally responsible, and socially acceptable, reducing uncertainty and strengthening the social license to operate.
  

DOCTORAL DEGREE IN NETWORK ENGINEERING

• SÁNCHEZ VITAL, ROGER: Contributions to energy-efficient multi-radio architectures for novel IoT scenarios
  
  Author: SÁNCHEZ VITAL, ROGER
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN NETWORK ENGINEERING
  Department: Department of Network Engineering (ENTEL)
  Mode: Normal
  Deposit date: 15/07/2025
  Reading date: 09/09/2025
  Reading time: 16:00
  Reading place: Sala d'actes (C4-001PG) de l'EETAC enllaç de Meet: https://meet.google.com/mbr-hgaj-wix
  Thesis director: GARCIA VILLEGAS, EDUARDO | GOMEZ MONTENEGRO, CARLOS
  Thesis abstract: As wireless networks continue to evolve to support a growing variety of applications, energy efficiency has become a critical design requirement, particularly for devices operating on constrained power sources. Effective energy management strategies are essential to enable sustained and reliable wireless communication across heterogeneous landscapes, where certain nodes must remain active over extended periods with minimal energy availability. These requirements become increasingly complex with the advent of next-generation Internet of Things (IoT) applications, which often introduce additional constraints such as reduced latency and increased bandwidth demands. Although Wi-Fi presents a potentially viable solution, it does not fully align with the needs of these applications, particularly in terms of energy consumption and communication range. Despite ongoing efforts by the IEEE P802.11 Working Group to tailor Wireless Local Area Network (WLAN) technologies for IoT contexts, the inherent trade-offs between energy efficiency and performance metrics, like data rate and latency, remain an unresolved challenge.A promising way to improve the energy efficiency of Wi-Fi-based IoT devices is to integrate a secondary radio. Said interface may be a simple, low-cost, ultra-low-power Wake-up Radio (WuR) or a Low Power Wide Area Network (LPWAN) technology (e.g., LoRaWAN). Its role is to allow the primary Wi-Fi radio to remain in a low-power sleep state for extended periods. In this multi-radio setup, the high-rate interface handles the transmission of application data, while the low-rate, energy-efficient interface extends its functionality by maintaining connectivity and managing wake-ups when necessary. This design allows the device to stay network-aware even when the main radio is inactive, to save energy. Even currently deployed IoT devices and appliances equipped with a single-radio Wi-Fi interface could be integrated into the proposed scheme through the use of softAPs, which are nowadays a common solution to provide connectivity. They allow any device with sufficient capabilities (e.g., smartphones) to act as a Wi-Fi Access Point (AP) running on a limited power source. To further extend device lifetime, particularly in dense network environments where AP activity significantly impacts energy consumption, this thesis explores the AP Power Save framework, which is under discussion by the IEEE 802.11bn Task Group (TGbn). Additionally, the LoRa Alliance has introduced Long Range-Frequency Hopping Spread Spectrum (LR-FHSS), a new physical layer modulation for LoRaWAN offering greater scalability and robustness for Satellite IoT use cases, among others. This thesis investigates whether LR-FHSS maintains the low-power characteristics required for energy-constrained IoT deployments.Analytical modeling and simulation results show that a multi-radio architecture incorporating a WuR as the secondary interface maintains latency figures comparable to conventional single-interface networks while significantly reducing energy consumption (by up to almost two orders of magnitude). Real-world device measurements further validate these findings. Additionally, the thesis presents an in-depth analysis of key energy-saving mechanisms proposed within the IEEE 802.11 TGbn, including Scheduled Power Save, (Semi-)Dynamic Power Save, and Cross-Link Power Save, among others. Open research challenges in this domain are also discussed. Numerical evaluations suggest that AP power consumption can be reduced by an average of one-third, with the possibility for further optimization. In parallel, the assessment of LR-FHSS reveals that although it may exhibit higher energy consumption than LoRa under certain conditions, it can nonetheless support long battery lifetimes when optimally configured. Specifically, with the appropriate payload size, LR-FHSS end devices can operate for many years on modest power sources like coin-cell batteries.
  

DOCTORAL DEGREE IN PHOTONICS

• KOKABEE, OMID: High-power ultrafast optical parametric oscillators from the visible to mid-infrared
  
  Author: KOKABEE, OMID
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN PHOTONICS
  Department: Institute of Photonic Sciences (ICFO)
  Mode: Normal
  Deposit date: 09/07/2025
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: EBRAHIM-ZADEH, MAJID
  Thesis abstract: In a synchronously pumped optical parametric oscillator (SPOPO), the pump laser pulses are timed to arrive at the OPO crystal in synchronism with the circulating signal pulses, enabling efficient energy transfer and the generation of high-power, high-repetition-rate, widely tunable, ultrashort pulses. This synchronization allows SPOPOs to achieve high conversion efficiencies and excellent temporal, spectral and spatial characteristics. The research presented in this thesis focuses on the development of high-power ultrafast SPOPOs at repetition rates from 76 MHz to as high as 1 GHz covering the visible to mid-infrared spectrum.First, we presented a method for efficient generation of femtosecond pulses with wide tuning in the red spectrum using a periodically-poled LiNbO3 (PPLN) as the nonlinear gain crystal combined with bismuth triborate (BIBO) for internal frequency doubling. High nonlinear gain in both PPLN and BIBO, combined with collinear pumping, results in a conversion efficiency of 17.2%, providing tunable coverage across the 665-785 nm range. The large spectral acceptance in PPLN and BIBO facilitates convenient wavelength tuning by adjusting the SPOPO cavity delay, without modifying other parameters such as PPLN crystal temperature, BIBO phase-match angle, or pump wavelength.Further, we reported the implementation of a femtosecond SPOPO operating at an approximate repetition rate of 1 GHz using a novel technique to enhance the MHz pump repetition rate. The system uses PPLN as the nonlinear medium and features an innovative cavity design exceeding the fundamental synchronous cavity length. Driven by a Kerr-lens mode-locked (KLM) Ti:sapphire laser operating at 76 MHz, the system generates near-transform-limited pulses at the 13th harmonic of the pump laser frequency, corresponding to 988 MHz. Internal dispersion compensation using a pair of SF11 prisms in the linear cavity configuration achieves stable near-transform-limited output signal pulses up to the 14th harmonic of the pump laser repetition rate, corresponding to 1064 MHz.Later, we introduced a universal method for maximizing output power from optical oscillators through interferometry. By incorporating an antiresonant ring interferometer into one arm of the oscillator cavity, continuously variable output coupling is achieved over a broad spectral range and under any operating conditions. Demonstrated using a femtosecond SPOPO, this technique enables continuously adjustable output coupling from 1% to 60%. At an optimized output coupling of approximately 30%, around 200 mW of power is extracted, more than double the output compared to a conventional output coupler with around 4%. The method maintains a Gaussian beam profile and near-transform-limited pulse durations.Additionally, we detailed the development and characterization of a highly efficient and stable picosecond SPOPO system based on magnesium oxide-doped PPLN (MgO:PPLN), pumped by a ytterbium (Yb) fiber laser. The system achieves exceptional performance in power output and conversion efficiency, with a total average power extraction of 11.7 W. This includes 7.1 W of signal radiation at 1.56 μm and 4.6 W of idler radiation at 3.33 μm, with a remarkable extraction efficiency of 73%. This performance is accompanied by superior spectral and spatial beam characteristics, exhibiting exceptional output power stability.
  

DOCTORAL DEGREE IN POLYMERS AND BIOPOLYMERS

• ARIOLI, MATTEO: Novel polyamides containing bio-based units: thermal properties, polymorphic transitions, chemical modifications and evaluation of processing conditions.
  
  Author: ARIOLI, MATTEO
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN POLYMERS AND BIOPOLYMERS
  Department: Department of Chemical Engineering (EQ)
  Mode: Normal
  Deposit date: 15/07/2025
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: FRANCO GARCIA, MARIA LOURDES
  Thesis abstract: Nylons, a class of linear polyamides, are well-known materials used in a huge number of different applications. Since the first production occurred during the last years of the 1940s, these polymers showed their ability to being used as technical polymers in the production of ropes, lines, nets, and injection molded pieces for the automotives industry and for household utensils. Their characteristic properties, such as the mechanical strength and the chemical and thermal resistance, are derived from their peculiar molecular conformations, characterized by the presence of strongly developed hydrogen bonds between the amidic groups of the macromolecules. The different organizations of the polymeric chains confer to nylons multiple crystalline structure. With the development of technology, nylons have been used for modern applications, such as in the 3D-printing technique, in the electronic field as triboelectric materials and in biomedicine as sutures, part of prosthetics, dental implants and catheters. In the last decades, greater attention has been devoted to the study of non-conventional nylons, based on monomers derived from bioresources or containing odd numbered carbon chains, enabling a deeper understanding of these materials and paving the way for new applications. In this sense, this doctoral thesis has been developed taking into account a new series of nylons, derived from biobased pimelic derivatives and containing monomers with a odd number of carbons. The work of the first part will be devoted to their synthesis, the crystalline characterization and the study of the thermal behavior and characterization, taking advantage of different techniques, including synchrotron light based analytical instruments. A second part of the thesis has been centered on the synthesis of poly(ester amide)s containing a bioactive triazole ring moiety. The inclusion of ester bonds in the macromolecular chains allows the introduction of a degradable group, obtaining a material that possesses the characteristic of a polyamide with the bio applicability of a polyester. The triazole ring, included in the macromolecules via a one-pot alkyne-azide click reaction, has been further studied for its bioactivity, as anti-microbial, anti-bacterial and anti-inflammatory agent. Lastly, a real application of a commercially used odd-even nylon has been tested. An injection molding machine has been used for in-situ X-ray measurement, by installing the equipment directly in a synchrotron beamline. With this configuration, the machine has been tested for direct study of the behavior of polymeric materials during the process of molding by injection.
  
• GAMBOA RIVERA, JILLIAN TRICIA: Development of conducting materials as electrodes for biomedical sensors
  
  Author: GAMBOA RIVERA, JILLIAN TRICIA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN POLYMERS AND BIOPOLYMERS
  Department: Department of Chemical Engineering (EQ)
  Mode: Normal
  Deposit date: 13/06/2025
  Reading date: 22/09/2025
  Reading time: 11:30
  Reading place: ESCOLA D'ENGINYERIA BARCELONA ESTSALA POLIVALENT EDIFICI IEDF. I, PLANTA 0, ESPAI I.0.1AVDA. EDUARD MARISTANY 16 (08019) BARCELONA934137400
  Thesis director: TORRAS COSTA, JUAN | ESTRANY CODA, FRANCISCO
  Thesis abstract: The cost of healthcare is an increasing concern worldwide, driven by the emergence of new diseases as well as the progression of lifestyle-related conditions. For this reason, expenditure on healthcare-related research is expected to rise over the next decade. One of the main lines of research is biosensors, which have shown great potential in improving patient care, as demonstrated by the success of sensors such as glucometers. Biosensors can aid not only in disease detection but also in the regular monitoring of a patient’s status.In this work, new materials based on conducting polymers and carbon quantum dots were developed for use as electrodes in various biosensors. The work is divided into four different parts, each focusing on a different material and application. In the first part, a thin film electrode was developed based on the carbon quantum dot doping of PEDOT, which was synthesized via electropolymerization. Doping quantity optimization and as well as chemical and morphological characterizations were performed on the films. The films were then deposited on substrate and on an organic electrochemical transistor for the electrochemical detection of dopamine. In the second part, carbon quantum dots were used in an immunosensor. The carbon quantum dots were first immobilized on the surface of a carbon electrode to enhance electroconductivity then functionalized with antibodies to obtain a highly selective sensor. Electrochemical and chemical characterizations were performed for each subsequent layer. Finally, the resulting immunosensor was tested against the D-dimer antigen via electrochemical impedance spectroscopy. The third and fourth parts focus on conducting polymer hydrogel, wherein the main hydrogel matrix was mixed with the conducting polymer, PEDOT:PSS, along with other additives. In the third part, the main hydrogel used was PVA modified with tannic acid for strength and carbon quantum dot for electroactivity enhancement; while the fourth part is a GelMA-based hydrogel modified with alginate. In both works, optimization of the additive amounts was performed and as well as the investigation of the individual and synergistic effects of the components on various characteristics such as mechanical and electrochemical properties. Finally, the PVA-based hydrogel was used as a pressure sensor, while the GelMA-based hydrogel was employed as a 3D cell culture platform for an impedance-based cell monitoring system.Overall, this PhD work demonstrated the application of various techniques and materials in the development of novel conductive biomaterials for biomedical sensors. These innovative materials could serve as a foundation for next-generation biosensors, with the potential to enhance patient care and quality of life.
  

DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS

• LLAVERIA GODOY, DAVID: Neural Network-Based Data Processing for Satellite Imagery in Small Satellite Earth Observation Missions
  
  Author: LLAVERIA GODOY, DAVID
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS
  Department: Department of Signal Theory and Communications (TSC)
  Mode: Article-based thesis
  Deposit date: 11/07/2025
  Reading date: 09/09/2025
  Reading time: 16:00
  Reading place: Sala de Graus ETSETB, Edifici C4, Campus Nord, Barcelona
  Thesis director: CAMPS CARMONA, ADRIANO JOSE
  Thesis abstract: The increasing availability and miniaturization of satellite sensors have enabled CubeSats to emerge as powerful platforms for Earth Observation (EO). Despite their reduced size and low cost, CubeSats can provide high-resolution geophysical information, provided that their intrinsic limitations, limited onboard power, processing capacity, storage, and downlink bandwidth, are effectively addressed. This thesis explores the development and implementation of efficient data processing methodologies that can operate under such constraints. By shifting part of the EO processing pipeline from the ground segment to the satellite itself, the goal is to enable autonomous, real-time analysis onboard, thus reducing the volume of data transmitted and increasing the timeliness and scientific value of satellite products.To this end, the thesis presents a series of algorithmic contributions spanning both traditional signal processing techniques and machine learning approaches, including neural networks. First, a lightweight deblurring methodology is proposed to mitigate image degradation caused by Attitude Determination and Control System (ADCS)-induced jitter in high-resolution optical CubeSat imagery. The method relies exclusively on inertial telemetry, estimating a spatially variant blur kernel and performing regularized deconvolution to restore image sharpness with minimal computational overhead.Second, the work introduces a two-stage neural network architecture to retrieve Sea Ice Concentration (SIC) and Sea Ice Extent (SIE) from L-band radiometric, and GNSS-Reflectometry (GNSS-R) data acquired by the FSSCat mission. The first network estimates coarse SIC/SIE maps using radiometry and auxiliary variables, while the second enhances resolution over GNSS-R reflection points, effectively combining the complementary strengths of both sensors.Third, the thesis proposes the Sequential Band Selection and Ranking (SBSR) algorithm for hyperspectral dimensionality reduction. This unsupervised method employs simple, interpretable metrics, entropy and spectral correlation, to iteratively select bands that maximize information content while minimizing redundancy. Its low computational complexity makes it well-suited for onboard execution.Finally, the SBSR approach is extended through a Convolutional Neural Network (CNN)-based model capable of performing band selection directly on coarsely aligned hyperspectral data, as typically encountered in pushbroom sensors onboard CubeSats. The CNN processes cross-correlation and autocorrelation matrices to produce band relevance scores, enabling robust selection without prior spatial co-registration.All methods were validated using real-world datasets from the PRISMA and FSSCat missions, as well as benchmark hyperspectral scenes (Indian Pines, Houston 2018). The results demonstrate that the proposed algorithms achieve comparable or superior performance to existing approaches while drastically reducing computational cost and data volume.
  

DOCTORAL DEGREE IN SUSTAINABILITY

• ROURA SALIETTI, MIREYA: Reuse of ICT devices as commons: A property rights governance model for collective access
  
  Author: ROURA SALIETTI, MIREYA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN SUSTAINABILITY
  Department: University Research Institute for Sustainability Science and Technology (IS.UPC)
  Mode: Normal
  Deposit date: 15/07/2025
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director:
  Thesis abstract: Understanding the role of property rights in managing Information and Communication Technology devices, primarily computers, is fundamental to addressing resource waste and achieving digital inclusion and sustainability goals. Although ICT device acquisition, use, and disposal are predominantly governed by individual property, reuse ecosystems demonstrate significant benefits. In such ecosystems, diverse actors collaborate to recover discarded ICT devices, refurbish, maintain and deliver them at minimal environmental and economic cost to vulnerable populations. Based on Common-Pool Resources theory, this thesis introduces a model that applies a community property approach to govern the reuse of ICT devices, using the bundle of rights framework to organise and manage reuse ecosystems. Building on the eReuse initiative, developed through action-research by a multistakeholder community involved in computer refurbishment for social inclusion in Spain, it captures patterns of collective action, classifies participants by roles, and maps the property rights underpinning their interactions, ensuring fair relationships within the ecosystem. To assess the suitability and application in Ibero-American contexts, the model was evaluated in three reuse ecosystems in Argentina and Uruguay. Results indicate that, although local adaptation is often needed, the model works in practice and shows strong potential to inform the governance design in culturally aligned ICT reuse ecosystems. The model is operationalised through two digital tools, DeviceHub and Workbench, which facilitate the tracing of property changes in devices throughout their life cycle, while also collecting detailed usage and performance metrics. In eReuse, it was found that approximately 46% of discarded and donated devices could be reused, highlighting the premature recycling of functional equipment due to criteria such as accounting or software obsolescence. Data collected through these tools also enables more precise estimation of impacts and supports the creation of indicators for comparing digital inclusion strategies across various regions and scenarios. The results show that the CO2 equivalent efficiency of reusing devices ranges from 30% in areas with a higher proportion of renewable energy to 5% in regions dependent on fossil fuels, when compared to new devices. This underscores that reuse is not inherently efficient but is instead dependent on contextual factors. Furthermore, these findings emphasize the need for more granular data to refine these estimates and gain a better understanding of the full impact of ICT reuse in different contexts. Finally, this governance model was tested through practical case studies in real-world contexts. Our results demonstrate that the success or failure of reuse depends on the sociocultural context and barriers such as ensuring long-term maintenance and usability, which are more effectively mitigated in servitised reuse ecosystems, where maintainers and ICT agents ensure device performance in the face of rapid technological change. These insights contribute to bridging the gap between sustainability goals and ICT governance, highlighting the role of digitally enabled reuse ecosystems in fostering equitable, low-carbon digital transitions and generating local employment opportunities.
  

DOCTORAL DEGREE IN THEORY AND HISTORY OF ARCHITECTURE

• GHAFFARI POUR JAHROMI, NEGIN: The geometry of vision: A comparative study of Persian architecture and miniature painting as a unified system (Ilkhanid and Timurid periods)
  
  Author: GHAFFARI POUR JAHROMI, NEGIN
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN THEORY AND HISTORY OF ARCHITECTURE
  Department: Department of History and Theory of Architecture and Communication Techniques (THATC)
  Mode: Normal
  Deposit date: 26/05/2025
  Reading date: 25/09/2025
  Reading time: 12:00
  Reading place: ETSAB (Escuela Técnica Superior de Arquitectura de Barcelona) - Planta Baja - Sala de Grados Av. Diagonal, 649-651 - 08028 - Barcelona
  Thesis director: AZARA NICOLAS, PEDRO
  Thesis abstract: This doctoral thesis explores the shared geometric foundations of Persian architecture and miniature painting between 1256 and 1550, spanning the Ilkhanid, Timurid, and early Safavid periods. It argues that both art forms are governed by a unified visual and symbolic system rooted in Persian cosmology and Islamic intellectual traditions.Combining historical research, visual analysis, and geometric reconstruction using tools such as AutoCAD, Illustrator, and Rhino, the study examines architectural structures (domes, iwans, courtyards) and miniature compositions side by side. Sources include architectural plans, treatises by mathematicians like Buzjani, Al-Biruni, and Al-Kashi, and illustrated manuscripts preserved in collections such as the Bibliothèque nationale de France.The thesis demonstrates that both architecture and miniature painting utilize similar spatial strategies—layered compositions, symbolic depth, and geometric order—eschewing linear perspective to create immersive, contemplative environments. It identifies recurring elements such as ornamental geometry, garden motifs, and architectural symbols across both media.Comparative case studies align miniature representations with real architectural sites, revealing formal and conceptual correspondences. These findings suggest that Persian visual culture operated as a coherent system where geometry functioned as both an aesthetic principle and a reflection of divine harmony.By bridging artistic and architectural traditions, the thesis contributes a new interdisciplinary model to Islamic art history and highlights the cultural continuity between intellectual, visual, and spatial practices in Persian civilization. The Geometry of Vision offers a new lens through which to understand how Persian visual culture articulates a unified geometry of space, symbol, and spirit.
  

DOCTORAL DEGREE IN THERMAL ENGINEERING

• RUANO PÉREZ, JESÚS: Novel dispersion error and Grey Area Mitigation approaches for subsonic jet noise spectra
  
  Author: RUANO PÉREZ, JESÚS
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN THERMAL ENGINEERING
  Department: Department of Heat Engines (MMT)
  Mode: Normal
  Deposit date: 14/07/2025
  Reading date: 05/09/2025
  Reading time: 11:00
  Reading place: Sala de Conferències del TR5, ESEIAAT (Carrer Colom 11, Terrassa)
  Thesis director: OLIVA LLENA, ASENSIO | TRIAS MIQUEL, FRANCESC XAVIER
  Thesis abstract: In Computational AeroAcoustics, scientists deal with a numerical error not always considered in other disciplines: the dispersion error. This error generates that waves with different frequencies travel at different speeds, distorting the acoustic spectrum.Additionally, new issues appear when turbulence modelling is added to the problem. Within the family of Detached Eddy Simulations (DES), the Gray Area Problem delays the transition from the RANS mode into the LES mode, generating non-physical oscillations that contaminate the full noise spectra.Here, we present a new methodology to numerically analyse and evaluate this error, without the primary constraint of being limited to structured uniform meshes, but also applicable to stretched ones. When applied to stretched grids, the extracted conclusions with this new method do not show a clear difference between high and low-order numerical schemes, as the former quickly degrades its order of accuracy. As an application case, we simulate a subsonic round jet using two different numerical codes: NOISEtte, which uses high-accuracy schemes, and OpenFOAM, an open-source code that uses low-order schemes. This case allows us to compare the effect that the order of the scheme has on the acoustic spectra of the subsonic round jet. Additionally, this case allows us to analyse how the selection of the filtering length scale and the turbulence model within a DES approach can act as a Gray Area Mitigation technique, conditioning the validity of the results.
  

DOCTORAL DEGREE IN APPLIED MATHEMATICS

• ABUASAKER, WALAA: A Contribution to Group Decision Aiding by means of Multi-Perceptual Unbalanced Linguistic Assessments.
  
  Author: ABUASAKER, WALAA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN APPLIED MATHEMATICS
  Department: School of Mathematics and Statistics (FME)
  Mode: Normal
  Deposit date: 28/07/2025
  Deposit END date: 08/09/2025
  Thesis director: SANCHEZ SOLER, MONICA | AGELL JANÉ, NÚRIA
  Thesis abstract: In decision-aiding environments under uncertainty, assessments are often expressed in linguistic terms whose meanings can vary significantly between individuals. In this thesis, this variation is modeled through the concept of a linguistic perceptual map, grounded in the lattice structure of hesitant fuzzy linguistic term sets. Each individual or group is associated with a unique linguistic perceptual map reflecting their interpretation of linguistic assessments. This doctoral research introduces a novel framework for projecting and aggregating individual assessments onto a common perceptual map, enabling the derivation of a central opinion and an associated measure of consensus. This thesis extensively studies the mathematical properties of the projection function. The thesis provides a theorem proving that the projection function is a monomorphism between lattices. In addition, it is also proven that this projection function preserves crucial order relations. Furthermore, this thesis progresses beyond existing research by introducing an interpretation function. This function facilitates the translation of the aggregated result from the common perceptual map back to each individual’s original linguistic perceptual map. The properties of the interpretation function are also subject to analysis, demonstrating its role in preserving previous order relations, despite not being a morphism. This doctoral research presents a multi-perceptual collective decision-aiding methodology built on the mathematical concepts introduced in this work. Finally, to illustrate the practicality of the proposed methodology, it is applied to three real-world case studies. The first analyzes data of ratings from the Amazon Books platform, the second considers data from the Too Good To Go platform to explore public interest in food waste reduction, and the third examines data of news coverage across European countries concerning the Israel-Gaza war.
  
• PARDO ARAUJO, MARTA: Understanding the Impact of Climate and Human Mobility on the Spread of Invasive Mosquito Vectors and Diseases
  
  Author: PARDO ARAUJO, MARTA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN APPLIED MATHEMATICS
  Department: School of Mathematics and Statistics (FME)
  Mode: Normal
  Deposit date: 28/07/2025
  Deposit END date: 08/09/2025
  Thesis director: BARTUMEUS FERRÉ, FREDERIC | ALONSO GIMENEZ, DAVID
  Thesis abstract: Global change, driven by climate shifts, habitat alteration, and human activity, has accelerated the spread of invasive species and pathogens into previously unaffected regions. Once established, these species can disrupt ecosystems, introduce diseases, and threaten public health and economies. In Europe, this has been evident through the COVID-19 pandemic and recent dengue outbreaks in Mediterranean countries. The latter driven by: the arrival and establishment of mosquito vectors, the subsequent regional spread of these vectors, and the arrival of infected individuals from dengue endemic areas. The combination of global transportation networks and increasingly favourable conditions for invasive species has made their tracking and prevention particularly challenging. In response, recent advances in technology and mathematical modelling have enhanced our ability to understand and address these challenges. This thesis investigates how climate and human mobility influence the spread of invasive mosquito vectors and associated diseases.Aedes mosquitoes are invasive vectors that are colonizing various regions in Europe. In this thesis we focus on: Aedes albopictus, Aedes aegypti, Aedes koreicus, and Aedes japonicus, with particular emphasis on Ae. albopictus, the main vector responsible for recent dengue outbreaks in Europe. As ectothermic organisms, mosquitoes are highly sensitive to environmental conditions; their development rates and the time needed to become infectious are strongly temperature-dependent. In this work, we examine how environmental factors, including temperature, rainfall, human population density, and land use, affect the population dynamics of these species and how these factors relate to their current spatial distribution. We calculated the mosquito reproduction number, which we used as an indicator of habitat suitability. Our results reveal that the four species possess unique thermal performance profiles. Ae. aegypti showed the highest optimal temperature, whereas \textit{Ae. japonicus} had the lowest. We further investigate the impact of human mobility on the spread of \textit{Ae. albopictus} in Spain using a metapopulation model enriched with high-resolution mosquito occurrence and human mobility data. Our results show that human movement is a key driver of mosquito spread, with both natural and human-mediated dispersal jointly promoting complex and multi-scale spreading. We observed a minor influence of climate on spread dynamics, highlighting dispersal as the primary factor shaping the spatial distribution of the species. Additionally, we identified a minimum temperature threshold of -12°C which hinders Ae. albopictus establishment. Finally, this thesis examines how human mobility affects disease spread within a connected system, considering two mobility types: commuting (short-term, round-trip movement) and migration (long-term or permanent relocation). By applying random matrix theory, we derived a threshold equivalent to the basic reproduction number and identified the main drivers of disease propagation. Our results show that the average commuting rate plays a crucial role in disease distribution across the system. This result aligns with our findings on mosquito invasion dynamics, where human mobility similarly governs the distribution of colonized patches.
  

DOCTORAL DEGREE IN ARCHITECTURAL, BUILDING CONSTRUCTION AND URBANISM TECHNOLOGY

• GONZÁLEZ ESPINOSA, VANESSA: Diseño de materiales cementícios reforzados con fibras vegetales impregnadas con materiales de cambio de fase para mejorar el comportamiento térmico de las cubiertas de los edificios.
  
  Author: GONZÁLEZ ESPINOSA, VANESSA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ARCHITECTURAL, BUILDING CONSTRUCTION AND URBANISM TECHNOLOGY
  Department: Department of Architectural Technology (TA)
  Mode: Normal
  Deposit date: 31/07/2025
  Deposit END date: 12/09/2025
  Thesis director: CLARAMUNT BLANES, JOSE | LACASTA PALACIO, ANA MARIA
  Thesis abstract: In the current context, sustainable construction prioritises innovative materials that combine energy efficiency, mechanical strength and safety against extreme conditions, such as fire, in order to address the challenges of climate change and human needs. Fibre-reinforced cementitious composites and phase change materials (PCM) are emerging as a promising solution, particularly in raised roof pavements, where thermal regulation is essential. The main objective of this thesis is to develop a cement board reinforced with non-woven vegetable fibres and PCM for raised roof pavements, determining the optimal dosage of cement, fibres and PCM that maximises mechanical resistance and thermal regulation capacity, as well as analysing its response to fire. The research seeks to advance the integration of PCM and plant fibres into cementitious matrices, proposing improvements for their practical application in construction with an environmental focus.The methodology, which is highly experimental in nature, was structured in several stages. First, the state of the art on cementitious composites and PCM was reviewed, identifying trends and challenges. Subsequently, an experimental campaign was designed that included: selection of materials (commercial cements, non-woven fibres and pure and microencapsulated PCMs), formulation of mixtures with different proportions of fibres and PCMs compared to a control without PCMs, evaluation of mechanical properties (flexural strength), thermal properties (conductivity, thermal storage and retardation) and fire behaviour through standardised tests, and statistical analysis to determine the impact of each component.The results show that the incorporation of PCM RT28 through direct impregnation into non-woven fibres in cementitious composites improves thermal properties, achieving a delay in temperature changes comparable to that of microencapsulated PCM mixed into the cementitious matrix. However, the composite made with PCM RT28 has superior mechanical strength, with a modulus of rupture (MOR) approximately three times greater than that of the microencapsulated composite, although both show a decrease in strength compared to samples without PCM. The non-woven fibres, by effectively impregnating the PCM, reinforce the cohesion of the composite and preserve hardening by deformation, partially mitigating the loss of mechanical strength.Although both the vegetal fibres and the PCM used are organic in nature and therefore combustible, the cementitious composites exhibited good fire performance, with low-intensity flames and a high self-extinguishing capacity once the heat source was removed. Overall, the samples with PCM incorporated through fibre impregnation showed better fire behaviour than those formulated with microencapsulated PCM: although ignition occurred slightly earlier, the total heat released (THR), as measured in the cone calorimeter tests, was substantially lower.This combination, which has been little explored, balances thermal efficiency and structural functionality, with direct applications in sustainable buildings. The research provides a detailed analysis of the interaction between plant fibres, PCM and the cement matrix, proposing optimal dosages and strategies to mitigate fire-related risks. The results lay the foundations for future research and practical applications, promoting the development of more efficient and sustainable building materials.
  
• ROODNESHIN, MARYAM: Strategies for urban progress toward higher renewable energy: a PV-centric approach with a clustering methodology. Case study in Barcelona
  
  Author: ROODNESHIN, MARYAM
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ARCHITECTURAL, BUILDING CONSTRUCTION AND URBANISM TECHNOLOGY
  Department: Department of Architectural Technology (TA)
  Mode: Normal
  Deposit date: 28/07/2025
  Deposit END date: 08/09/2025
  Thesis director: MUROS ALCOJOR, ADRIAN | MASSECK, TORSTEN ANDREAS
  Thesis abstract: This dissertation presents a comprehensive study on the integration ofintegrating photovoltaic (PV) systems within urban environments, focusing on Barcelona as a case study. It explores innovative approaches to strivingachieving for nearly 100%higher renewable energy adoption by leveraging a PV-centric methodology enhanced through clustering strategies. The research emphasizes emphasises the interplay between architectural design, construction techniques, and urban planning to optimize optimise energy efficiency and utilizationutilisation, addressing critical environmental challenges such as CO2 emissions and air pollution.Through the integration of computer simulations, literature reviews, and empirical analyses, the study evaluates Barcelona’s solar potential and the impact of morphological indicators—such as density, building height, and orientation—on energy performance. The findings provide actionable insights for urban planners and architects, proposing advanced solar grid designs that minimize minimise reliance on fossil fuels while promoting sustainable urban development.A GIS-based framework integrates urban spatial data to assess solar potential and financial viability, incorporating parameters such as building density, height, and orientation A GIS-based framework is employed to assess the solar potential and financial viability of PV systems across five representative Barcelona neighbourhoods, incorporating a detailed analysis of a specific area within each neighbourhood. By modelling district-specific characteristics and optimizing optimising urban layouts, the study identifies key factors influencing energy efficiency, including urban form and energy capture/dissipation dynamics. A clustering strategy organizes organises PV arrays based on proximity and solar energy uniformity using algorithms like K-means and 3D proximity, striking a balance between energy production, cost, and environmental impact.Optimization Optimisation scenarios evaluate PV system parameters—such as module dimensions, tilt, orientation, and spacing—assuming multi-crystalline silicon (mc-Si) technology with 20% efficiency. Key constraints, including roof occupation limits, maximum ground coverage ratios, and shading reduction, are addressed to enhance energy yield, efficiency, and cost-effectiveness. The evolutionary algorithm within Grasshopper’s Galapagos component refines system designs by analysing metrics such as Levelizedised Cost of Energy (LCOE), energy yield, and CO2 emissions.The research introduces the concept of “solar neighbourhoods,” emphasizing emphasising the integration of reduced energy consumption and maximized maximised energy production through strategic urban design. Findings The findings highlight the critical role of neighbourhood geometry, orientation, and compactness in optimising PV panel placement and improving environmental performance. By reducing ground coverage ratios, enhancing energy production, and ensuring financial viability, these strategies contribute to the development of resilient and sustainable urban landscapes.This study bridges the gap between theoretical research and practical applications, offering a roadmap for urban planners and policymakers to integrate PV systems and renewable energy solutions into city development. Recommendations include optimizing optimising urban layouts, tailoring building geometries, and enhancing solar exposure to address energy and environmental challenges. By aligning financial, environmental, and operational considerations, the research provides a holistic framework for fostering sustainable urban development and resilience, charting a path toward greener, energy-efficient global cities.
  

DOCTORAL DEGREE IN ARTIFICIAL INTELLIGENCE

• BAGHERZADE GHAZVINI, MINA: A Data-driven Intelligent Decision Support Framework for Process Operation Management. An Application to Gas Turbine Process.
  
  Author: BAGHERZADE GHAZVINI, MINA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ARTIFICIAL INTELLIGENCE
  Department: Department of Computer Science (CS)
  Mode: Normal
  Deposit date: 25/07/2025
  Deposit END date: 05/09/2025
  Thesis director: SANCHEZ MARRE, MIQUEL | ANGULO BAHON, CECILIO
  Thesis abstract: This thesis presents a data-driven framework for enhancing the management and maintenance of industrial processes, exemplified through a case study involving gas turbines. The research focuses on several key areas: preprocessing operational data, identifying operational modes, analysing transitions between these modes, and detecting patterns for predictive maintenance. The research proposal begins with detailed data preprocessing to ensure the quality and usability of data. It then introduces methods for automatically recognising distinct operational modes using an ensemble of clustering techniques The research also explores the modelling of transitions between these operational states, capturing the dynamic nature of industrial processes. Furthermore, the Cluster-based Matrix Profile method is proposed to detect significant operational patterns that indicate potential issues or efficiencies, essential for developing predictive maintenance strategies. Overall, the framework developed in this thesis offers a systematic approach to improve decisionmaking, reliability, and efficiency in managing industrial processes. Although initially applied to gas turbines, this framework holds the potential for broader applications across various industrial systems.
  

DOCTORAL DEGREE IN CIVIL ENGINEERING

• GAHIMA, STEPHAN: Data-Driven Patient-Specific Models Supporting Decision Making with Application to Atherosclerotic Plaque Analysis
  
  Author: GAHIMA, STEPHAN
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN CIVIL ENGINEERING
  Department: Barcelona School of Civil Engineering (ETSECCPB)
  Mode: Normal
  Deposit date: 30/07/2025
  Deposit END date: 10/09/2025
  Thesis director: DIEZ MEJIA, PEDRO | GARCIA GONZALEZ, ALBERTO
  Thesis abstract: This thesis advances finite element-based tools to improve atherosclerosis analysis by addressing current computational limitations. Atherosclerosis, the leading cause of ischaemic heart attacks, imposes a significant social and economic burden (estimated at around $1 trillion worldwide by 2030). In this disease, patients develop plaques from lipid accumulation in the arteries and these plaques can be prone to rupture or stable. Differentiating between these types is essential for effective clinical risk management.Fast, accurate, and robust computational methods can streamline the clinical pipeline and ultimately may help to assess atherosclerotic analysis. We use Finite Element Method (FEM) to simulate stress in atherosclerotic sections, as peak stress plays a key role in assessingrupture risk. Our methods are based on unfitted FEM, which simplify mesh generation, save computational and pre-processing time. Importantly, these methods can work directly on voxelized data such as medical images. The proposed unfitted approaches achieve accuracy within 5 % of that attained by classical fitted approaches and commercial software, for both linear and non-linear cases. Moreover, these methods incorporate a flexible and realistic boundary conditions that account for the influence of surrounding tissues. We also developed an Adaptive Model Reduction (AMR) technique based on a linear hypothesis, serving as a preliminary step toward creating fast surrogate models for near-real-time simulations.Validation experiments demonstrate that AMR decrease computational resource usage by over 70 % while maintaining an accuracy within a 9 % error margin compared to high-fidelity models. Finally, preliminary results indicate that using Topological Data Analysis (TDA) to build interpretable Machine Learning (ML) models can effectively assesses plaque rupture risk. Early experiments yield a classification accuracy of approximately 75 %, a performance comparable to established radiomics approaches.Overall, this doctoral work demonstrates that combining advanced FEMs with interpretable ML may provides nuanced insights into atherosclerotic plaque assessment. Future research should address potential limitations such as data variability and scalability to enable broader implementation of these computational techniques in clinical practice.
  

DOCTORAL DEGREE IN CONSTRUCTION ENGINEERING

• COLLAO LAZO, JORGE ALEJANDRO: Application of BIM visual programming algorithms for infrastructure projects
  
  Author: COLLAO LAZO, JORGE ALEJANDRO
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN CONSTRUCTION ENGINEERING
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 29/07/2025
  Deposit END date: 09/09/2025
  Thesis director: LOZANO GALANT, JOSE ANTONIO | TURMO CODERQUE, JOSE
  Thesis abstract: The BIM digitization has generated a growing automation of traditional AECO project development processes. However, this automation has mainly benefited building projects, which has generated a critical gap in infrastructure projects, such as (1) bridges, (2) roads, and (3) tunnels. This gap is explained by infrastructure projects' lack of standardization compared with building projects. Recently, the BIM industry has incorporated conventional computer programming as a tool capable of partially reducing this lack of automation, developing code-line algorithms. However, both the work interface and the high technical skills required to produce these scripts have been unfriendly to AECO industry professionals. To resolve this gap, BIM software development companies generated an alternative algorithm creation technique called Visual Programming (VP). This technique creates their scripts through visual expressions, represented as process charts instead of the code lines of conventional programming, optimizing the working interface of different human resources from AECO projects. However, the development of VP algorithms for infrastructure projects is still limited.To fill these gaps, the objective of this thesis will be to study the potential automation of infrastructure project processes, developing an integrated platform between VP algorithms and BIM models.At a general level, the platform proposed by this thesis has the following 2 elements: (1) VP algorithms; These custom scripts have the specific function of processing information from external databases and deliver specific data as outputs, and (2) BIM models; These information models will digitally collect the outputs of the VP algorithms and associate them with specific BIM families of the infrastructure projects under study. This thesis focuses on studying transversal problems of Civil Engineering using VP-BIM tools through the development of the following applications:Firstly, this thesis develops a calculation module to estimate (1) greenhouse (GHG) emissions; these pollutants contribute to global warming and climate change by trapping heat in the Earth's atmosphere [1–3] and (2) carbon footprint for vehicle traffic on specific roads in any country with the appropriate traffic and vehicle fleet data. The main novelty of this module is the automated integration of the GHG emission factors recommended by the European Environmental Agency (EEA) TIER 1 level with specific fleet data through a customized VP script. This proposed module was applied on a road in Barcelona (Spain), and the results were compared with a similar study made by the Barcelona transport agency. In addition, specific calculation modules were developed to measure the impact of emission reduction strategies.The second application developed by this thesis aims to use visual programming as an educational tool. A parametric programming workflow is employed to replicate the structural behavior of a beam within a BIM Model. This approach enables students to visualize and analyze structural performance, fostering a deeper connection between classroom theory and hands-on experimentation. This system aims to improve the visualization and understanding of structural data for AEC industry professionals by generating dynamic 3D and 2D models. The educational impact of this tool was assessed through a survey conducted in a structural analysis course at the University of La Serena (Chile), demonstrating its effectiveness in enhancing student comprehension and engagement with modern engineering practices.
  
• DEL CARLO, FEDERICA: He.R.A. Heritage at Risk Assessment: Vulnerability Estimation of Masonry Churches for Multi-Layer Single Risk Analysis
  
  Author: DEL CARLO, FEDERICA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN CONSTRUCTION ENGINEERING
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Change of supervisor
  Deposit date: 25/07/2025
  Deposit END date: 05/09/2025
  Thesis director: ROCA FABREGAT, PEDRO | CAPRILI, SILVIA
  Thesis abstract: This research was developed in response to the increasing need for coherent and integrated methodologies to assess the complex and multifaceted risks threatening cultural heritage. Three critical issues were identified at the outset. The inconsistency in terminology and the absence of standardised definitions across risk analysis frameworks, hindering both comparability between studies and the development of actionable strategies. The scarcity of methodologies capable of addressing a large number of heritage architectures, resulting in time and cost-intensive risk assessments that are tailored to specific architectural contexts and difficult to apply elsewhere. The prevailing preference for methodologies that focus on single hazardous events often overlooks the potential for cascading or compound events, despite current risk management guidelines advocating for the integration of multi-event information in planning and preparedness strategies. To address these gaps, the research proposes a quantitative methodology for regional-scale physical vulnerability estimation, specifically targeting seismic and landslide vulnerabilities in historical churches. The adopted methodology is based on a multilayer single-hazard framework, aiming to harmonise and standardise risk analysis procedures. Physical vulnerability is expressed through an index-based approach that combines event intensity indicators with churches physical resistance indicators. While seismic and landslide phenomena are analysed independently, both are evaluated within a shared conceptual approach, which enables direct comparison and prioritisation across hazardous events. Three main phases can be identified. First, the risk context is defined by identifying the objectives, study area characteristics, and hazardous event types. A consistent and scalable data collection process is designed, including the creation of a survey form tailored to masonry churches. The survey form draws on literature-based indicators and existing vulnerability analysis methodologies to support systematic and standardised data gathering for a large building sample. Second, event-specific physical vulnerability indices are developed and validated. The seismic vulnerability index draws on a regression-based model informed by nonlinear static analyses performed on archetypes derived from a typological classification. Generalised Linear Models (GLMs) are employed to relate the probability of failure to churches main geometric attributes. The resulting seismic physical vulnerability index represents the expected tendency of vulnerability over a properly selected range of intensities. The landslide vulnerability index is adapted from an existing method and recalibrated using resistance indicators specifically selected for historical churches. Both indices range into a 0–1 scale and allow for comparability within prioritisation and disaster risk reduction frameworks. Finally, the methodology is extended to estimate scenario-based risk for earthquake-triggered landslides, combining the landslide vulnerability index with susceptibility data and uniform exposure. This scenario-based approach enables the estimation of risk without requiring information on the frequency of the triggering events. The full methodology is applied to a case study in northern Tuscany, a region characterised by high seismicity and widespread slope instability, encompassing 71 surveyed masonry churches. Results reinforce the value of an integrated yet adaptable vulnerability analysis strategy.
  
• ELNAGGAR, OMAR AHMED MAHMOUD: Framework for Optimizing the Construction Process in Saudi Arabia: The Integration of Lean Construction, Building Information Modeling (BIM), and Emerging Technologies
  
  Author: ELNAGGAR, OMAR AHMED MAHMOUD
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN CONSTRUCTION ENGINEERING
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 25/07/2025
  Deposit END date: 05/09/2025
  Thesis director: TURMO CODERQUE, JOSE | ATENCIO CASTILLO, EDISON PATRICIO
  Thesis abstract: The construction industry in Saudi Arabia is experiencing rapid growth driven by the ambitious Vision 2030, but challenges related to inefficiencies, cost overruns, and delays persist. This research presents a comprehensive framework designed to optimize the construction process in Saudi Arabia by integrating Lean Construction, Building Information Modeling (BIM), and Emerging Technologies. Through an extensive review of 64 academic papers, this research identifies key tools and methodologies within Lean, BIM, and Emerging Technologies, that have been successfully applied in construction management. However, it also highlights the absence of a comprehensive framework that effectively integrates these domains in a structured manner.The research was developed through the Design Science Research Method (DSRM) and proposes a novel framework that categorizes these elements across the four phases of construction: Plan, Design, Construct, and Operate. This integration seeks to align functionality, optimize processes, and enhance lifecycle efficiency, while addressing the limitations of current approaches. The framework initially evaluated through expert consensus using the Delphi Method and subsequently tested in a real-world case study of a confidential mega-scale project in Saudi Arabia during the Design phase. Using pre-defined Key Performance Indicators (KPIs) such as cost efficiency, time efficiency, productivity, waste reduction, quality and safety, stakeholder satisfaction, and process automation, the study provides insights into the practical impact of the framework in improving project outcomes.The findings demonstrate the potential of the integrated framework to reduce waste, improve collaboration, and optimize overall project performance. This research contributes to the advancement of construction project management in Saudi Arabia by proposing a transformative approach that integrates Lean, BIM, and Emerging Technologies, offering practical recommendations for stakeholders seeking to enhance their construction processes. This framework aims to guide the Saudi construction industry in overcoming existing challenges and achieving more efficient, cost-effective, and high-quality project outcomes.Expert evaluations and practical applications validate the effectiveness and relevance of the framework, highlighting its potential to revolutionize construction management in Saudi Arabia and offering a robust model for other regions encountering similar challenges.
  
• FARRE CHECA, JOSEP: Analysis of Cantilever Construction of Concrete Cable-Stayed Bridges with Time-Dependent Phenomena
  
  Author: FARRE CHECA, JOSEP
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN CONSTRUCTION ENGINEERING
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 28/07/2025
  Deposit END date: 08/09/2025
  Thesis director: TURMO CODERQUE, JOSE | LOZANO GALANT, JOSE ANTONIO
  Thesis abstract: This work presents a study on the construction analysis of cable-stayed bridges built by the cantilever method, with a particular focus on the effects of time-dependent phenomena such as creep and shrinkage. In the design of these structures, construction analysis is essential, as the highest stresses and deflections typically occur during the erection process, rather than in service. Therefore, accurately simulating the construction sequence is necessary to ensure structural safety and reliability. However, many existing analysis tools have limitations, such as difficulties in isolating and evaluating individual construction stages, high computational time and storage requirements, and the dependence on global iterative procedures to reach the final target state. These challenges make the construction simulation process both time-consuming and restrictive.To address these limitations, this research proposes and develops efficient computational methods for simulating the construction process of cable-stayed bridges. A first method, referred to as the Direct Algorithm, is presented for use in cases where time-dependent effects are neglected. This algorithm allows for the independent simulation of each construction stage without relying on the superposition principle or on information from previous or subsequent stages.When time-dependent effects such as creep and shrinkage must be considered, the Forward-Direct Algorithm is proposed. This method enables the simulation of the construction process while accounting for long-term concrete behavior, and does so without requiring iterative procedures to adjust the tensioning forces.One of the main contributions of this work is the definition of new criteria for the Objective Service Stage, understood as the target geometry and stress state of the bridge at a specific time. These criteria consider both the cantilever construction process and the influence of time-dependent phenomena. The aim is to establish a tensioning strategy that requires only a single prestressing operation for each stay cable, thereby avoiding costly and complex tuning operations either at the end of construction or during the service life of the structure.The proposed algorithms and criteria are validated through a case study based on the geometry of a real bridge design, analyzed under different construction scenarios. The results confirm the accuracy and reliability of the Direct Algorithm and the Forward-Direct Algorithm in predicting structural behavior during both construction and service. Comparisons with traditional analysis methods from the literature highlight the advantages of the proposed approaches in terms of both precision and computational efficiency. This research offers practical tools and strategies for improving the design and construction of cable-stayed bridges, particularly those built with cast-in-place concrete and erected using the cantilever method, where time-dependent effects play a significant role.
  

DOCTORAL DEGREE IN EARTHQUAKE ENGINEERING AND STRUCTURAL DYNAMICS

• CHAVEZ AGUIRRE, JEAN PIERS NICOLAS: Post-Earthquake Functional Recovery and Resilience of Seismically Isolated Hospitals and Large-Scale Building Portfolios
  
  Author: CHAVEZ AGUIRRE, JEAN PIERS NICOLAS
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN EARTHQUAKE ENGINEERING AND STRUCTURAL DYNAMICS
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 25/07/2025
  Deposit END date: 05/09/2025
  Thesis director: LOPEZ ALMANSA, FRANCISCO | MURCIA DELSO, JUAN
  Thesis abstract: This dissertation presents a comprehensive contribution to assessing and optimizing the functional resilience of both individual hospital buildings and urban-scale building portfolios. The research addresses critical challenges in post-earthquake recovery by combining probabilistic methodologies, optimization algorithms, and machine learning techniques to evaluate and enhance the performance of hospital facilities, as well as assess large building portfolios with unprecedented computational efficiency. The first core contribution of this work lies in the development of a probabilistic framework for assessing the post-earthquake functionality of seismically isolated hospital buildings. Recognizing that traditional assessment methods and resilience metrics overlook complex interdependencies among non-structural components, medical equipment, and utilities, this study employs Bayesian Networks (BNs) to model such dependencies explicitly. The proposed framework quantifies the probabilistic damage of over 60 equipment and component types based on ground motion parameters, and propagates their impact through critical hospital departments. The framework allows for the direct computation of functionality indices using damage outputs.Building upon the proposed functionality loss model, the research also introduces a multiobjective optimization framework for hospital recovery planning using the NSGA-II genetic algorithm. The framework addresses the challenge of optimal labor allocation by minimizing both repair time and cost. It enables decision-makers to define the number of workers per repair group based on the importance of each component, which is classified according to its contribution to total functionality loss. The solution space is explored through a high-dimensional search of work effort allocations, and Pareto-optimal repair plans are obtained. The results indicate that excessive labor deployment yields diminishing returns in repair time while significantly increasing cost, with differences in repair time under design basis earthquake and maximum considered earthquake remaining below 13%.To address the scalability of resilience assessments at the urban scale, the dissertation proposes the Urban Cluster Earthquake Resilience (UCER) framework, which leverages unsupervised machine learning algorithms for regional seismic risk and resilience evaluation. Applied to a dataset of 23420 reinforced concrete and masonry buildings in a synthetic urban environment in Italy, the framework employs t-distributed stochastic neighbor embedding (t-SNE) for dimensionality reduction, HDBSCAN for density-based clustering, and K-Medoids for robust cluster representation. This process reduces the analysis complexity from thousands of buildings to 398 representative clusters. The results and findings of this dissertation highlight the benefits of integrated, data-driven approaches for assessing seismic resilience. By combining probabilistic interdependence modeling, artificial intelligence, and urban clustering, this research bridges the gap between detailed building-level assessments and large-scale regional resilience planning. Ultimately, the findings support the development of more resilient healthcare infrastructures and cities by enabling decision-makers to rely on scientifically grounded tools to prepare, respond, and recover effectively from seismic disasters.
  

DOCTORAL DEGREE IN ELECTRICAL ENGINEERING

• BADRI BARBERÁN, JOSÉ ANTONIO: Development of a methodology for optimizing transformers and devices with magnetic core
  
  Author: BADRI BARBERÁN, JOSÉ ANTONIO
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ELECTRICAL ENGINEERING
  Department: Department of Electrical Engineering (DEE)
  Mode: Normal
  Deposit date: 25/07/2025
  Deposit END date: 05/09/2025
  Thesis director: RIBA RUIZ, JORDI ROGER | GARCIA ESPINOSA, ANTONIO
  Thesis abstract: This thesis contributes to the field of design and optimization of magnetic core devices, specifically transformers for power electronics. A calculation software has been developed for the design of transformers, based on an analytical-parametric geometric, electromagnetic, thermal model of the main components of a transformer: the core and windings. Experimental studies have been carried out to analyze the magnetic losses in transformer cores, evaluating the contribution of the different constructive parts as well as the impact of voltage harmonics on the magnetic losses of the core. In addition, hysteresis and other loss models have been developed to improve the accuracy of core loss estimation. For the coils, electromagnetic (skin and proximity) and thermal effects have been modelled. Through experimental studies and simulations, the interaction between the temperature and frequency-dependent effects on winding resistance have been analyzed. These studies have demonstrated that winding losses can be, in fact, analytically and accurately calculated. Once a detailed design has been obtained, the core and winding losses are entered into a thermal model to predict the operating temperature of the transformer. After concluding the analytical-parametric model, a real-world industrial applications-oriented optimization system has been implemented. This system allows both single-objective and multi-objective optimization on any desired transformer parameter, always ensuring compliance with the technical and operational needed requirements through constraints. The optimization system has been validated using real cost-optimized prototypes and the results obtained have been compared with experimental tests, demonstrating the accuracy and reliability of the calculation system developed, and allowing its applicability in actual industrial manufacturing processes.
  

DOCTORAL DEGREE IN ELECTRONIC ENGINEERING

• FORNT MAS, JORDI: Designing Deep Learning Accelerators in the limits of Energy Efficiency
  
  Author: FORNT MAS, JORDI
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ELECTRONIC ENGINEERING
  Department: Department of Electronic Engineering (EEL)
  Mode: Normal
  Deposit date: 25/07/2025
  Deposit END date: 05/09/2025
  Thesis director: MOLL ECHETO, FRANCESC DE BORJA | ALTET SANAHUJES, JOSEP
  Thesis abstract: Deep Neural Network (DNN) models form the backbone of today’s Artificial Intelligence (AI) systems. Their large size and high computational cost have resulted in specialized hardware accelerators being essential for executing these models across many applications. However, the energy efficiency of state-of-the-art accelerator systems falls short of the demands of current AI, especially considering that, while DNN models keep getting larger and more complex, Moore’s Law is coming to a halt. This thesis aims at investigating new ways of optimizing the energy efficiency of AI accelerators by considering and leveraging different degrees of freedom involved in the computation of DNN workloads. Namely, several energy efficiency optimization techniques are explored involving accelerator dataflow, functional circuit approximations, low-bit quantization, mixed-precision, and undervolting; with the goal of pushing the limits of energy-efficient AI acceleration.
  

DOCTORAL DEGREE IN GEOTECHNICAL ENGINEERING

• YAZDANI CHERATI, DAVOOD: Hydromechanical Simulation of Argillaceous Rocks for Radioactive Waste Disposal Applications
  
  Author: YAZDANI CHERATI, DAVOOD
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN GEOTECHNICAL ENGINEERING
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 28/07/2025
  Deposit END date: 08/09/2025
  Thesis director: VAUNAT, JEAN | GENS SOLE, ANTONIO
  Thesis abstract: Argillaceous claystones are primarily composed of clay particles of sedimentary origin andcontain a substantial amount of chemically precipitated cement, often calcium carbonate, whichacts as a bonding agent. Due to their favorable properties—such as low permeability, minimalmolecular diffusion, self-sealing capabilities, and high retention capacity for radionuclides—theyare considered suitable host geomaterials for the deep geological disposal of radioactive waste.However, fractures within these geomaterials, induced by excavations or post-disposal processes,can create preferential pathways for radionuclide migration, potentially influencing theperformance of the disposal system. Therefore, these problems should be numerically evaluated.However, due to their complex behavior, modeling argillaceous rocks presents a significantchallenge. Under shearing, these geomaterials exhibit anisotropy, creep, and quasi-brittle failurecharacterized by significant post-peak softening and strain localization. This study aims toinvestigate the hydromechanical response of Callovo-Oxfordian (COx) argillaceous claystones tolaboratory tests, field excavations, and post-disposal processes by employing the argillite modelsimplemented in the CODE-BRIGHT program. The argillite models are adopted since they caneffectively reproduce the key characteristics of argillaceous materials. Additionally, throughoutthis thesis, several other constitutive models are applied to simulate the behavior of materialsinteracting with the COx, including soft and rigid supports, and swelling materials. The outcomesof this thesis provide significant insight into the hydromechanical behavior of argillaceous rocks,thereby contributing to a more accurate evaluation of the disposal process.
  

DOCTORAL DEGREE IN MATERIALS SCIENCE AND ENGINEERING

• GARCÍA DE ALBÉNIZ LÓPEZ DE ABERÁSTURI, NEREA: Engineering zirconia surfaces with cell instructive and antibacterial properties
  
  Author: GARCÍA DE ALBÉNIZ LÓPEZ DE ABERÁSTURI, NEREA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN MATERIALS SCIENCE AND ENGINEERING
  Department: Department of Materials Science and Engineering (CEM)
  Mode: Article-based thesis
  Deposit date: 29/07/2025
  Deposit END date: 09/09/2025
  Thesis director: JIMENEZ PIQUÉ, EMILIO | MAS MORUNO, CARLOS
  Thesis abstract: Tetragonal zirconia polycrystals stabilized with 3 mol% yttria (3Y-TZP) has gained growing interest as an alternative to titanium for dental implants, owing to its excellent biocompatibility, high mechanical strength and corrosion resistance and superior aesthetics. Despite these advantages, the clinical performance of zirconia implants still depends on their ability to promote osseointegration while simultaneously minimizing the risk of bacterial colonization, a competitive process known as "race for the surface". Surface properties of dental implants, such as topography, chemistry, and wettability, critically influence the biological response at the tissue-implant interface. In particular, micro- and nanotopographies directly impact cell-material interaction and can modulate several cellular functions including adhesion, migration, proliferation, and differentiation. Similarly, these topographical features affect bacterial response, either promoting bacterial adhesion or, conversely, reducing colonization through antifouling or bactericidal effects. For this reason, surface modifications have become a widely explored strategy to enhance the biological performance of implants. Nevertheless, the major challenge lies in designing surfaces that simultaneously support osseointegration while also preventing bacterial adhesion.This PhD Thesis addressed this challenge by investigating different surface modification approaches to improve the biological performance of zirconia. The aim was to create topographies that simultaneously improve cell behavior while exhibiting antibacterial properties. In concrete, we developed and characterized a series of micro and nanostructured zirconia surfaces and evaluated their biological performance both in terms of human mesenchymal stem cell (hMSC) response and bacterial adhesion of different strains. Prior to experimental work, a comprehensive bibliographic review on topographical modification strategies for 3Y-TZP was conducted (Chapter I), highlighting existing knowledge gaps and guiding the selection of surface treatments. Following this, different surface modification techniques were employed, including hydrofluoric acid (HF) etching for generating nanotopography (Chapter II) and laser patterning via nanosecond (ns-) and femtosecond (fs-) laser to create defined microstructures (Chapter III). These techniques were also combined to evaluate a potential synergistic effect of hierarchically rough micro- and nanotopographies on the biological response (Annex I). Our findings demonstrate both chemical etching and laser patterning techniques successfully enhanced the biological performance of zirconia by improving the hMSCS behavior and reducing bacterial adhesion. However, their combination did not result in a synergistic improvement. Among all the surfaces, the 3 μm linear pattern (L3) created through fs-laser patterning offered the best balance by simultaneously enhancing hMSC adhesion, migration, and osteogenic differentiation, while significantly reducing the adhesion of Staphylococcus aureus and Pseudomonas aeruginosa bacteria. It also led to the most favorable biological outcome under competitive co-culture conditions. Furthermore, biofunctionalization of this topography using a multifunctional peptide containing both antimicrobial and cell-adhesive sequences showed promising synergistic biological effects (Annex II). Importantly, these improvements were achieved without compromising the mechanical integrity of the L3-patterned surface (Annex III). In conclusion, this PhD Thesis demonstrated that topographical modification of zirconia offers promising strategies for developing zirconia implant with improved biological performance, enhancing both osseointegration and antibacterial properties. Future directions should focus on integrating biochemical cues, in vivo validations, and complete assessment of the mechanical integrity.
  

DOCTORAL DEGREE IN PHOTONICS

• KARANIKOLAOU, TERESA DIMITRA: Heating and decoherence due to light scattering in atomic media
  
  Author: KARANIKOLAOU, TERESA DIMITRA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN PHOTONICS
  Department: Institute of Photonic Sciences (ICFO)
  Mode: Normal
  Deposit date: 25/07/2025
  Deposit END date: 05/09/2025
  Thesis director: CHANG, DARRICK
  Thesis abstract: Cold atom platforms have become central to quantum technologies such as information processing, simulation, and metrology. Their versatility and high degree of control make them especially powerful. A key breakthrough in the field was the ability to trap individual atoms using light. Far-off-resonant optical dipole traps—like optical tweezers and lattices—enable precise positioning of atoms in diverse geometries, from simple 2D arrays to complex 3D structures. Another major advantage of cold atoms is their ability to mediate interactions between photons, which do not naturally interact in free space. Cold atomic ensembles act as a nonlinear medium, enabling strong interactions even at the two-photon level. Using collective atom-photon coupling and Rydberg-state excitations, they allow for photon-photon gates and the creation of non-classical states of light. These two features—strong optical nonlinearities and precise atomic positioning—make cold atoms a leading platform for quantum networks, quantum simulations, and studies of light-matter interaction.A phenomenon common to both platforms is photon scattering, which can either be of an intended or unintended nature. Up until recently, simple theories of scattering were sufficient for the community. However, the advance of atomic platforms now requires more nuanced and sophisticated theories to understand scattering and their consequences on applications. This constitutes the main theme of the thesis. In the application of atom trapping, in many practical situations atoms may experience state-dependent potentials. The potential mismatch can lead to excess heating and reduced elastic scattering of light, as compared to well-known limits like an atom in “magic-wavelength” traps or a trapped ion. In the first part of the thesis, we develop a model to analyze these effects, which can have important consequences in quantum optics or in atom imaging.In the second part of the thesis, we investigate how Rydberg spin waves decohere in the presence of light scattering, within the context of Rydberg Electromagnetically Induced Transparency (EIT). Within Rydberg EIT, an initial photon is stored as a coherent, extended superposition across atoms. This initial photon can strongly modify the propagation of subsequent photons, leading to large nonlinearities, but the scattering of subsequent photons can reveal information about where the first photon was stored, leading to decoherence of the initial superposition state. This in turn can lead to decreased utility or ability to retrieve the first photon. Here, we elucidate the nature of decoherence, and in particular for the first time we take fully into account the three-dimensional nature of the ensemble and its multiple scattering of light. We find regimes in which multiple scattering might offer additional protection from decoherence, as compared to previous simplified theories. Overall, this thesis makes new advances in understanding the nature of microscopic atom-light interactions and scattering, and connects this fundamental physics to key consequences in real-life applications.
  

DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS

• FELGUEIRAS LUIS, DIANA ZAIDA: Magnetohydrodynamics enhanced radio blackout mitigation system for spacecraft during planetary entries
  
  Author: FELGUEIRAS LUIS, DIANA ZAIDA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS
  Department: Department of Signal Theory and Communications (TSC)
  Mode: Normal
  Deposit date: 28/07/2025
  Deposit END date: 08/09/2025
  Thesis director: CAMPS CARMONA, ADRIANO JOSE | CHAZOT, OLIVIER
  Thesis abstract: Spacecraft entering planetary atmospheres are enveloped by a plasma layer with high levels of ionization, caused by the extreme temperatures in the shock layer. The charged particles in the plasma interact with electromagnetic waves emitted by onboard antennas, resulting in communication and tracking difficulties during flight and causing radio communication blackouts that can last several minutes. The magnetic field alleviation technique is a proposed solution to reduce the plasma layer effects on radio signal propagation. This technique involves superimposing a magnetic field onto the plasma flow, transforming it into an anisotropic medium and altering its refractive index. This enables the creation of an extraordinary wave capable of propagating at plasma frequencies higher than the radio signal frequency.The Horizon 2020 Magnetohydrodynamic Enhanced Entry System for Space Transportation (MEESST) project aims to design and test a high-temperature superconducting (HTS) magnet to mitigate radio communication blackout and reduce surface heat flux. This research focuses on the experimental study of the radio communication blackout phenomenon and its mitigation using an applied magnetic field, in the VKI plasma wind tunnel. A tailored communication system, designed to accommodate the ionization levels encountered in ground testing, is developed and fully characterized in the UPC anechoic chamber.The results are divided into three main parts, each addressing a specific research question. The first part is dedicated to studying signal propagation in a plasma flow. Both air and CO2 plasma flows are characterized using emission spectroscopy. Radial temperature profiles are derived from the intensity of an oxygen atomic line, while electron number density profiles are determined from the Stark broadening of the Hb line. Radio signal magnitude profiles are measured in various configurations (side-to-side and stagnation) across a frequency range of 33 GHz to 40 GHz, under a wide range of testing conditions. Attenuation and Faraday rotation caused by the plasma are estimated, and the results show a strong correlation with the measured plasma frequencies.The second part examines the effects of an applied magnetic field on the plasma flow and radio signal propagation. The probe houses the HTS magnet, which can generate a maximum magnetic flux density of approximately 0.45 T at the front of the antenna. Characterization of the magnetized air plasma flow reveals an increase in radiance, stagnation heat flux, and plasma temperature and frequency, attributed to the applied magnetic field. The higher electron density near the antenna and the increased attenuation of the extraordinary wave result in negligible differences in signal attenuation profiles. However, changes are observed in the reflection coefficient depending on the magnetic field strength, and in the Faraday rotation depending on the field direction.The third part explores methods to duplicate flight conditions in ground facilities, concerning aerothermochemistry and radio communication blackout. A relevant condition related to radio blackout during the ARD reentry flight is selected, at an altitude of 60.6~km. The shock layer around an ARD model is replicated in the JAXA HIEST shock tunnel. The condition is numerically simulated for both flight and ground scenarios, highlighting the limitations of the binary scaling methodology. For the same flight condition, the local heat transfer simulation methodology is applied and tested in the Plasmatron facility, successfully replicating the same flow conditions. Finally, the electron number density profiles from both facilities are compared with those from flight.
  
• RAJA KUMAR, DHEERAJ: AI-Driven Multi-Antenna Designs for Next Generations of Wireless Communication Systems
  
  Author: RAJA KUMAR, DHEERAJ
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS
  Department: Department of Signal Theory and Communications (TSC)
  Mode: Normal
  Deposit date: 25/07/2025
  Deposit END date: 05/09/2025
  Thesis director: ANTON HARO, CARLES | MESTRE PONS, FRANCESC XAVIER
  Thesis abstract: As wireless networks evolve toward sixth-generation (6G) systems, the integration of advanced technologies like massive MIMO, millimeter-wave communication, intelligent reflecting surfaces, and massive multiple access schemes has led to significant increases in system complexity. Traditional signal processing and optimization techniques are grounded in explicit modeling and mathematical tractability. They increasingly fall short in addressing the high-dimensional, dynamic, and often non-linear behaviors of these systems. To bridge this gap, Artificial Intelligence and Machine Learning (AI/ML) methods have emerged as powerful alternatives, capable of learning directly from data and adapting to complex and uncertain environments.Rather than relying solely on conventional models or pure data-driven solutions, this dissertation advocates for hybrid approaches that combine model-based structures with learning-based flexibility. Hybrid methods mitigate the high data demands and limited interpretability of black-box models while overcoming the rigidity and assumptions of traditional schemes. This balance makes them particularly well-suited for the complex, imperfectly modeled conditions encountered in wireless systems.This PhD dissertation focuses on applying such hybrid methods to four key tasks in the wireless signal processing chain: channel estimation, symbol detection, digital precoding, and hybrid beamforming. Though each task poses unique technical challenges, they collectively contribute to the overarching goal of enabling robust, efficient, and scalable communication in next-generation systems.The first objective addresses channel estimation, a foundational task in massive MIMO systems where performance hinges on accurate knowledge of the channel state. In highly dynamic or non-linear environments, traditional estimators like LS or MMSE are often inaccurate. This work proposes low-complexity neural network architectures, specifically 1D-CNNs and Graph Neural Networks (GNNs), that serve as hybrid estimators by embedding structural insights while learning to compensate for model mismatches, showing strong performance across varying MIMO configurations.The second objective explores symbol detection in Rate-Splitting Multiple Access (RSMA), where receivers must decode a common message followed by private streams. The conventional RSMA receivers use successive interference cancellation (SIC) or joint detection schemes, that are capable of detecting all streams simultaneously. These are theoretically superior, but computationally infeasible in large-scale systems. To balance performance and complexity, this work introduces deep receiver architectures such as RS-Net+, which combine the interpretability of SIC with the adaptability of neural networks. These hybrid designs exhibit robustness to channel impairments and outperform both purely model-based and black-box neural schemes under linear and non-linear channel conditions.The third and fourth objectives focus on designing precoding techniques for RSMA, both in fully digital and hybrid analog-digital beamforming settings. Standard approaches like WMMSE, though effective, are iterative and computationally intensive. This thesis proposes self-supervised learning frameworks, based on GNN and MLP architectures, that learn precoding policies directly from channel data while respecting underlying model structures. These methods are then extended to hybrid beamforming scenarios, where learned digital precoders work in tandem with fixed analog beamformers to provide scalable and energy-efficient solutions.In summary, this dissertation advances the design of hybrid AI/ML solutions for core signal processing tasks in wireless communication systems. By combining domain knowledge with learning, it delivers architectures that are robust, interpretable, and well-suited to the challenges of future 6G networks.