Theses authorised for defence

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 AUTOMATIC CONTROL, ROBOTICS AND VISION

• CONEJO BARCELO, CARLOS: Functional Safety for Highly Automated Vehicles
  
  Author: CONEJO BARCELO, CARLOS
  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 AUTOMATIC CONTROL, ROBOTICS AND VISION
  Department: Department of Automatic Control (ESAII)
  Mode: Normal
  Deposit date: 30/06/2025
  Reading date: 21/07/2025
  Reading time: 10:00
  Reading place: Sala d'Actes de la Facultat de Matemàtiques i Estadística (FME) Campus Diagonal Sud, Edifici U. C. Pau Gargallo, 14 08028 Barcelona
  Thesis director: PUIG CAYUELA, VICENÇ | MORCEGO SEIX, BERNARDO
  Thesis abstract: The rapid advancement of autonomous vehicle technologies offers significant opportunities to improve road safety, but also introduces challenges to ensure compliance with established safety standards. This thesis focuses on guaranteeing functional safety in highly automated vehicles (SAE Levels 4-5), ensuring adherence to ISO~26262, which governs safety risks in electrical and electronic systems.To address these challenges, this work introduces a behavior tree-based supervisor that transforms static functional safety analyses into runtime monitoring, ensuring real-time compliance with safety requirements. The supervisor is formally verified using temporal logic to guarantee correctness under all operational conditions. Furthermore, a zonotopic LPV-EKF observer is developed for robust fault detection and isolation, improving the reliability of sensor-based vehicle state estimation under bounded uncertainties. Complementing these contributions, a data-driven zonotopic predictive control framework with functional safety guarantees is proposed. This framework integrates reachability analysis to guide vehicles toward predefined safe states in the presence of system-level anomalies and is formally verified through temporal logic specifications.The methodologies presented are validated on autonomous Renault Zoe and Mégane platforms, demonstrating their practical effectiveness in ensuring functional safety in autonomous driving under real-world scenarios.
  

DOCTORAL DEGREE IN CHEMICAL PROCESS ENGINEERING

• ROA TORRES, ALEXANDRA: Acidic Mining Waters as Resource Recovery for Sustainable Supply of Raw and Critical Materials
  
  Author: ROA TORRES, ALEXANDRA
  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: Article-based thesis
  Deposit date: 05/05/2025
  Reading date: 22/07/2025
  Reading time: 11:00
  Reading place: Campus Diagonal Besòs, Edifici I - EEBE - Sala Polivalent - Edifici I https://meet.google.com/jpq-rjky-mff
  Thesis director: CORTINA PALLAS, JOSE LUIS | LÓPEZ RODRÍGUEZ, JULIO
  Thesis abstract: Over the past years, the treatment of Acidic Mine Waters (AMWs) has gained a new interest as they can be used as a secondary source for Critical and Strategic Raw Materials (CRMs and SRMs, respectively). This, along with the fact that the European Union (EU) is promoting circular approaches to move towards a green economy, has shifted the application of traditional treatments towards the development and implementation of a circular scheme for the valorisation of AMWs. The proposed treatment scheme consisted of four main stages. A first pre-treatment stage, consisting on the removal of transition metals is based on two steps, the first one focused on the removal of Fe and Al as hydroxides, followed by another one for the removal of metals as sulphides. Both steps attained metal removals >90% for Fe, Al, Zn, Cd and Cu. The second stage is focused on the recovery of Rare Earth Elements (REEs). To selectively extract and concentrate them, ion exchange (IX) was applied. In this step, two commercial IX resins such as the TP272 (impregnated resin) and the S930 (chelating resin) were evaluated for the fractionation of REEs into Heavy (HREEs) and Light (LREEs). After the regeneration, the REEs were recovered by crystallizing them as oxalates to avoid the precipitation of other transition and/or rare earth alkaline ions present in the eluate. For that, oxalic acid and NH3 were used, achieving recoveries >95% from the eluate and the solids were a mixture of REEs, with purities >90%. In addition, an optimisation of the solution used during the regeneration process of IX resins was carried out to improve the concentration factors (CF), and to reduce the chemical consumption during the crystallization.The third stage focused on the reclamation of water. For that, different polymeric nanofiltration (NF) membranes (dnF40 under hollow fibre configuration, and NF270, NFX, and PRO-XS2 under flat-sheet configuration) have been used to evaluate the recovery of water with different levels of hardness removal. This consisted of the removal of Mn and Mg as hydroxides, using NaOH, followed by the removal of Ca as carbonate, using NaHCO3. During the removal of Mg, efforts were made to optimize its crystallization by using different concentrations of NaOH. The NF experiments showed rejection values >96%, except for the dnF40. However, when working in concentration mode, the formation of scaling was observed during the tests, which was related to the precipitation of calcium sulphate mineral phases. An additional effort was performed to evaluate the use of NF membranes with different active layer chemistry (e.g. semi aromatic amides (Desal DL), sulphamide (Desal KH) and polysthersulphonated (e.g. AMS3012, AMS3014) for the recovery of CRMs from other acidic streams such as Lithium-Ion Batteries (LIB) lixiviates. For that, two key aspects were evaluated, the type of leaching acid (H2SO4 and HCl) and the alkali used to neutralize the excess of acidity (NaOH versus Mg(OH)2(s)). The tests showcased a high impact of the solution chemistry in NF processes for LIBs recycling, as when Mg(OH)2(s) was used in HCl media, Li rejections of -77% were achieved, while these rejections were of -14% under H2SO4 media. The last stage of the proposed scheme for AMWs treatment focused on the valorisation of waste brines to produce acidic and basic solutions by Electrodialysis with Bipolar Membranes (EDBM) that later could be used in the other stages of the treatment. From this stage, solutions of 0.5 mol/L of NaOH and 0.45 mol/L of H2SO4 were attained as well as a salinity reduction of 58%. These tests highlighted EBDM as a sustainable approach for AMWs valorisation, as it promotes resource recovery, reduces the discharge of sulphates and hazardous wastes, and provides that circular approach to mining and water treatment industries that the EU is promoting.
  

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: pending
  Reading time: pending
  Reading place: pending
  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
  
• LI, SIYU: Urban Freight Distribution Management and Pricing with Tradable Mobility Credits
  
  Author: LI, SIYU
  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: 03/07/2025
  Reading date: 23/07/2025
  Reading time: 11:00
  Reading place: UPC North CampusBarcelona School of Civil EngineeringC/ Jordi Girona 1-3Building B1, room 005Barcelona
  Thesis director: ROBUSTÉ ANTÓN, FRANCESC
  Thesis abstract: Cities around the world are still facing increasing congestion problems. Emerging demands of ecommerce and other commercial activities make this situation worse. Congestion pricing schemes gain low public acceptance due to inequity. We introduce tradable mobility credit scheme as an alternative, which explicitly incorporates logistics users. Credits should be allocated to individuals with demonstrated travel demand, such as licensed drivers, while also accounting for the distinctive behaviors and externalities of urban delivery vehicles.A novel tradable mobility credit scheme and model is developed, integrating both individual and logistics users. We pay particular attention to externalities arising from non-compliant curbside delivery activities, including public space occupancy and traffic influence. The proposed scheme is tested through simulation. Results indicate that the framework enables logistics users to internalize delivery-related externalities, reduces overall congestion and encourages mode shifts among individual users. Comparative analysis of allocation strategies demonstrates that demand-based allocation yields higher overall efficiency and net social benefits, with manageable cost impacts on the logistics sector. Stakeholder interviews with citizens, experts and industry representatives further evaluate the political, technical and social feasibility of the scheme. Our findings suggest high technical readiness and generally positive social acceptance if the scheme is perceived as fair and beneficial. However, political challenges remain, particularly regarding potential resistance from the logistics sector.This research addresses critical gaps in the literature by integrating logistics users into the tradable mobility credits framework, providing empirical insights into mixed-user policy design and feasibility. The study concludes with recommendations for future research, including quantitative user selection analysis and modeling adaptive logistics behaviors.
  
• SIGLER LEIBOWITZ, LAURENCE: Advancing Decision Support: Content Management, Ecommerce, and the Challenge of Interoperability for Integrated Modeling
  
  Author: SIGLER LEIBOWITZ, LAURENCE
  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: 26/06/2025
  Reading date: 24/07/2025
  Reading time: 11:00
  Reading place: Sala Zienkiewich (CIMNE) Edificio C1, UPC - Campus Nord, Gran Capitan S/N 08034 Barcelona
  Thesis director: MORA SERRANO, FRANCISCO JAVIER | UBACH DE FUENTES, PERE ANDREU
  Thesis abstract: Computational modeling helps us understand how decisions influence outcomes by replicating complex processes with the necessary level of detail. Advances in technology now enable increasingly sophisticated models, making it possible to address complex problems that were previously out of reach. A key application is modeling natural and built environments, which function as interconnected systems-of-systems (SoS) with high-impact challenges. By replicating these problems through modeling, users can construct ad hoc workflows, combining models, computing, programming, data resources, and services as needed. Integrating model-based analysis into the study of these challenges shifts the focus from data-driven assessment to model-driven scenario evaluation. This requires predictive tools capable of assessing the consequences of different conditions by facilitating interoperability between resources. However, interoperability in computational modeling remains a challenge, requiring standardized data access, metadata harmonization, and service integration, with much work remaining to be done by the modeling community.This research aims to analyze, propose, and implement solutions for integrated, model-based interoperability to support the analysis of complex problems. It involves designing a theoretical platform framework that enables the structured interaction of models, data, and computational resources to support both scientific research and decision making. A key aspect of this work is the development of the concept and prototype of a marketplace where stakeholders can integrate, access, and commercialize resources, promoting collaboration and expanding the platform’s functionality. The research includes a detailed analysis of use cases to identify requirements and constraints, ensuring that the proposed solutions address practical challenges. Beyond analysis, it also involves the practical integration of a use case to demonstrate the applicability of the framework in a real world context. The integration of these use cases will validate the concepts explored earlier in the dissertation through practical application in a real-world situation and infrastructure, testing the framework’s effectiveness in a practical context.The study produces three key findings. First, it presents the theoretical design of an integrated modeling framework that supports interoperability between computational models, datasets, and processing services. The framework establishes a structure for resource discovery, execution workflows, and user interaction while enabling metadata-driven service integration. Second, it demonstrates the feasibility of a modeling marketplace that supports resource discovery, acquisition, and reuse. The marketplace provides access to computational models, datasets, and processing services within a unified environment, allowing providers to distribute modeling resources while ensuring access control and licensing mechanisms.Third, it examines the integration of computational models within the European Commission’s Destination Earth initiative. DestinE’s approach to metadata standardization and service orchestration leads development of integrated modeling environments. These findings indicate that a theoretical framework for integrated modeling, incorporating computational models, a marketplace, and interoperable services, is technically viable. The research contributes to the development of modeling ecosystems that support decision-making through structured data access, model execution, and service integration.
  

DOCTORAL DEGREE IN COMPUTATIONAL AND APPLIED PHYSICS

• OJER FERRER, JAUME: The Effect of Social Interactions on Collective Behavior: From Flocking to Opinion Polarization
  
  Author: OJER FERRER, JAUME
  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 COMPUTATIONAL AND APPLIED PHYSICS
  Department: Department of Physics (FIS)
  Mode: Normal
  Deposit date: 26/06/2025
  Reading date: 30/07/2025
  Reading time: 12:00
  Reading place: Sala Teleensenyament, Edifici B3 , Campus Nord
  Thesis director: PASTOR SATORRAS, ROMUALDO | STARNINI, MICHELE
  Thesis abstract: Like viruses, information, knowledge, and emotions disseminate through a population, and the social interactions between individuals can give rise to a rich tapestry of collective behavior. Usually, we are able to ascertain the way in which individuals interact at a local level. Nevertheless, understanding how behavior emerges as a global feature is much more difficult and requires notions of synergy and complexity. This thesis investigates how social interactions shape collective behavior in social systems, focusing specifically on flocking dynamics in animal groups and opinion polarization in human societies. We employ theoretical frameworks derived from statistical physics and network science to analyze how local interaction rules lead to emergent phenomena, leveraging empirical data to validate our findings.In the context of animal behavior, we use social networks to represent the interactions within the flock. We extend the definition of Vicsek-like models to explore the effects that structural properties of social networks have on flocking stability. Networks with higher heterogeneity exhibit a more resilient ordered state, showing a diverging transition threshold, whereas lower heterogeneity renders the system more susceptible to external perturbations, showing a threshold converging to a finite value. However, if networks are weighted, analytical predictions extracted from the heterogeneous mean-field approximation reveal that the flocking threshold may also approach zero, i.e., a system that is always found in the disordered phase. Numerical simulations confirm these results. Finally, by considering real-world animal social networks, we show that networks with heterogeneous weights tend to exhibit a heightened sensitivity to noise, indicated by lower transition thresholds.Next, in the context of human behavior, we address the dynamics of opinion formation and polarization using a multidimensional perspective. To this aim, we use empirical opinions with respect to many different topics collected by the American National Election Studies. By mapping the opinions within a two-dimensional ideological space, we provide a nuanced analysis of how ideological polarization evolves over time in the United States. We assess the widening ideological gap between Democrats and Republicans over the past 30 years, highlighting an increase in within-party heterogeneity, particularly among Democrats. These findings contradict the partisan sorting hypothesis, which suggests that parties have become more consistent and ideologically more homogeneous in last decades.Lastly, we study the conditions under which polarization or consensus emerges by introducing the multidimensional social compass model. The model incorporates multiple opinion dimensions, each one corresponding to a distinct topic. A phase transition from polarization to consensus is exhibited at a critical threshold of social influence. However, correlations between multidimensional opinions play a pivotal role in the dynamics of depolarization. We demonstrate that if initial opinions are uncorrelated, the transition to consensus can be discontinuous depending on the number of dimensions, whereas if correlated, the transition is always continuous. Moreover, simulations of the model on top of social networks with a heterogeneous pattern of contacts indicate a vanishing threshold in the thermodynamic limit, in full agreement with the perturbation theory. We also explore the role of influential nodes in the depolarization process. We show that the presence of hubs can substantially lower the threshold value, effectively facilitating consensus. Conversely, when they hold divergent opinions, the social influence required to depolarize the system increases significantly.
  

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 CONSTRUCTION ENGINEERING

• LIU, GUANZHI: Recycled Polypropylene Fibre-Reinforced Concrete: From Recyclability and Recoverability to Materials and Application.
  
  Author: LIU, GUANZHI
  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: 03/06/2025
  Reading date: 25/07/2025
  Reading time: 12:00
  Reading place: DECA - B1-003
  Thesis director: DE LA FUENTE ANTEQUERA, ALBERTO | TOSIC, NIKOLA
  Thesis abstract: In recent decades, fibre-reinforced concrete (FRC) has played a significant role in construction due to its enhanced residual flexural tensile strength in comparison to plain concrete. However, with the increasing use of FRC, the dismantling of FRC structures is becoming an important challenge. Unlike plain and reinforced concrete, the recycling of FRC produces two primary by-products: recycled fibres and recycled aggregates with embedded fibres. Despite its significance, limited research has been conducted on the reuse of these by-products in new concrete. To address this research gap, this thesis focuses on polypropylene fibre-reinforced concrete (PPFRC) as a case study and examines its recycling process and the reuse of the resulting recycled materials.Initially, PPFRC was produced (parent concrete) and recycled by analysing the quantity and morphology of the recovered fibres and recycled aggregates. These recycled materials were used to produce new concrete (with recycled aggregates and recycled fibres) that was characterized, and the results were compared with the mechanical properties of the parent concrete. The findings revealed that the properties of concrete using recycled materials were reduced to different extends compared with the parent concrete.However, when different ratios of recycled fibres were incorporated into concrete, the mechanical properties showed significant improvement compared to using 100% recovered fibres, particularly at a fibre content of 3 kg/m³. Moreover, hybrid -virgin and recycled- fibre concretes outperformed those made entirely with virgin fibres. Thus, under certain conditions, it is feasible to replace virgin fibres with recovered fibres while maintaining or even enhancing mechanical performance.Furthermore, this thesis compares the mechanical properties and microstructure of new FRC made with recycled FRC aggregates to concretes made with natural aggregates and conventional recycled concrete aggregates. Concrete incorporating recycled FRC aggregates demonstrated advantages in fibre distribution at lower fibre contents. However, at higher fibre contents, the embedded fibres were found to have a detrimental effect. Micrographs and chemical dot plots revealed unique characteristics at the interface between the recycled aggregates and the fresh cement paste, highlighting changes in hydration and porosity compared to samples made with natural aggregates and conventional recycled aggregates.Future work on recycled FRC could include exploring the durability and long-term stability of the material, as well as investigating the potential application of recycled fine aggregates in concretes. 
  

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: pending
  Reading time: pending
  Reading place: pending
  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.
  

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: pending
  Reading time: pending
  Reading place: pending
  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

• ARIAS GARCIA, FRANCISCO ITURIEL: THERMOFORMING PROCESS ANALYSIS FOR IN-MOLD ELECTRONICS DEVICES
  
  Author: ARIAS GARCIA, FRANCISCO ITURIEL
  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: Normal
  Deposit date: 20/05/2025
  Reading date: 25/07/2025
  Reading time: 12:00
  Reading place: ESCOLA D'ENGINYERIA DE BARCELONA EST meet.google.com/rsw-jvxw-aoa Edifici I. Sala Polivalent I Planta 0 (I.0.1) https://eebe.upc.edu/ca/lescola/com-ar
  Thesis director: FONTDECABA BAIG, ENRIC
  Thesis abstract: In-Mold Electronic technology enables the creation of three-dimensional shaped electronic surfaces by combining printed electronics with In-Mold Decoration. This innovative approach enables the integration of electronic circuits into a wide range of complex and diverse applications, going from automotive interiors to consumer electronics. The manufacturing process for IME devices demands that all materials involved, including adhesives, endure the rigorous transformation conditions to ensure functionality and reliability of the final device. Adhesives, while critical for securing surface-mounted components and maintaining circuit integrity, possess properties that can significantly influence film deformation during the thermoforming process. These deformations can have a great impact on the overall performance and durability of the device. This research is dedicated to thoroughly examining the effects of the structural adhesive on film deformation during the thermoforming process, as well as the subsequent impact on device functionality. The study meticulously investigates how varying quantities and disposition placements of structural adhesives affect the film’s stretching behaviour during both thermoforming process and injection molding, comparing printed and hybridized samples. The research findings reveal that hybridized samples, those with structural adhesive, exhibit deformation patterns distinct from printed samples. Specifically, areas around the adhesive show reduced stretching, while regions farther from the adhesive compensate with increased stretching. This compensation often leads to overstretching in certain areas, which, in some cases, results in circuit discontinuities and compromised electrical performance. Moreover, the variation in stretching not only affects the circuit integrity but also alters the final positioning of electronic components. This misalignment can cause components to shift from their intended locations, potentially leading to device malfunctions or failures. To address these challenges, the study recommends adjusting the amount and placement of structural adhesive based on localized deformation patterns. By tailoring the adhesive application, unnecessary stretching can be minimized, ensuring both the mechanical and electrical integrity of the device. Additionally, further analysis during the injection molding process highlighted that careful management of adhesive quantity effectively secures all components in their designated positions without compromising functionality. The insights gained from this research are critical for the design and manufacturing of IME devices. They provide guidelines for optimizing adhesive placement and quantity, ultimately enhancing the reliability, performance, and yield of functional devices in high-volume production.
  
• 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 ESTC/Eduard Maristany, 16 (08019 Barcelona)Sala Polivalent EDIFICI IPlanta 0 eSPAI i.0.1https://eebe.upc.edu/es
  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 de Tesines (aula C1-002) Escola Tècnica Superior d'Enginyeria de Camins, Canals i Ports 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

• JAVED, FARHANA: Blockchain-enabled Trustworthy Inter-Provider Agreements for End-to-End Network Slicing in 5G and Beyond Networks
  
  Author: JAVED, FARHANA
  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: 03/07/2025
  Reading date: 30/07/2025
  Reading time: 11:00
  Reading place: Aula 001, edifici EETAC, campus Baix Llobregat, UPC
  Thesis director: MANGUES BAFALLUY, JOSEP
  Thesis abstract: The evolution toward Sixth Generation (6G) networks promises transformative advancements in performance and flexibility, enabling rapid and transparent resource scaling across multiple administrative domains. Central to this transformation are technologies such as Network Function Virtualization (NFV), which enable dynamic orchestration of network services and promote infrastructure sharing among diverse stakeholders. Initiatives like CAMARA and the GSMA Open Gateway framework exemplify the shift toward collaborative, multi-vendor ecosystems, where network capabilities and APIs are exposed across organizations to enhance interoperability. However, the cross-domain nature of service provisioning introduces new challenges, with trustworthiness emerging as a key requirement—particularly where operators must dynamically acquire resources from peer networks while maintaining service quality and controlling operational costs.This thesis addresses the research question: How can blockchain and DLT-based smart contracts enable a decentralized marketplace for automated, trustful service level agreements between multiple stakeholders in 6G networks toward end-to-end (E2E) network slicing? In response, this work contributes to the development of trustworthy, automated inter-provider agreements for next-generation networks by proposing a hybrid decentralized framework based on Distributed Ledger Technologies (DLTs). The solution aligns with 6G architectural visions and standardization efforts, including the NGMN Alliance’s emphasis on trust by design and ETSI’s initiatives on permissioned ledgers for telecom applications. Advancing beyond existing blockchain solutions, the framework integrates public and private blockchain infrastructures to balance transparency and confidentiality. It supports the full lifecycle of decentralized inter-provider agreements: participant registration, service negotiation, SLA monitoring, breach management, and financial settlement—laying the foundation for trustworthy service orchestration across heterogeneous domains.We first formalize the requirements for decentralized inter-provider agreements, which inform the design of a hybrid architecture combining public Layer 1, public Layer 2, and private Layer 1 blockchains. At its core, we develop a modular Decentralized Framework realized through a DApp integrating components such as the Credential Manager, Blockchain Adapter for off-chain data handling, Data Storage Layer, and Privacy Manager. Unlike conventional DApps, our framework explicitly addresses the challenges of integrating blockchain with telecom infrastructure. Key focus areas include secure off-chain data handling, real-time SLA monitoring, and mapping telco operations into blockchain-based smart contracts. Modular contracts are designed and deployed across blockchain layers to support domain registration, service listing, SLA monitoring, breach logging, penalty calculation, and secure financial transactions. This end-to-end architecture for trustworthy inter-provider agreements forms the first group of contributions.The second group of contributions validates and benchmarks the framework across real blockchain environments. We evaluate smart contract deployment and DApp operation on public Layer 1, public Layer 2, and private Layer 1 platforms, focusing on gas usage, transaction latency, scalability, and privacy overhead under realistic conditions. Additionally, we assess the framework’s suitability for continuous monitoring use cases, including collaborative AI/ML scenarios such as Federated Learning (FL), which require frequent, secure interactions in emerging 6G applications. From this extensive evaluation, we derive operational guidelines and design trade-offs that optimize for cost-efficiency, scalability, and confidentiality. These insights serve as a reference for blockchain-enabled service orchestration in future 6G networks.
  

DOCTORAL DEGREE IN PHOTONICS

• ENDERS, MICHAEL THOMAS: Tailoring the Direction and Polarization of Mid-Infrared Thermal Emission with van der Waals Materials
  
  Author: ENDERS, MICHAEL THOMAS
  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: 04/07/2025
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: PAPADAKI, GEORGIA
  Thesis abstract: The mid-infrared spectral region holds significant potential for applications in energy harvesting and waste-heat recovery, radiative cooling, spectroscopy, sensing, thermal camouflage and night vision, among others. Conventional approaches to controlling mid-infrared (mid-IR) radiation with metamaterials and metasurfaces often rely on intricate fabrication methods. Commercial components for mid-IR photonics rely on materials that limit their scalability and accessibility. In this thesis, we explore how van der Waals (vdW) heterostructures, with their intrinsically anisotropic optical properties and deeply subwavelength thicknesses, enable unprecedented manipulation of thermal emission in terms of directionality, polarization, and chirality.We first introduce a straightforward far-field method to extract the complex dielectric function of microscopic exfoliated flakes, facilitating accurate characterization of highly dispersive polar materials without sophisticated near-field instrumentation. We demonstrate how ultrathin flakes of α-molybdenum trioxide (α-MoO₃) can serve as deeply subwavelength phase retarders in the mid-IR, enabling efficient polarization control at spectral regions inaccessible to conventional bulk optical components. Moreover, we show that by simply twisting two anisotropic flakes, intrinsic mid-IR chirality can be engineered, resulting in circular dichroism in both absorption and thermal emission, effectively transforming inherently incoherent blackbody radiation into circularly polarized emission.Finally, we develop structures based on anisotropic dielectric spacers within Salisbury screen configurations, enabling simultaneous control over the azimuthal and zenithal angles of emitted thermal radiation. Through analytical and numerical analysis, clear design principles are derived and validated using realistic materials. The results presented here establish vdW materials and their heterostructures as versatile platforms for advanced mid-infrared photonic applications, significantly enhancing our capability to precisely tailor thermal radiation across a broad range of practical applications.
  

DOCTORAL DEGREE IN POLYMERS AND BIOPOLYMERS

• 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.
  
• MADHANI MOHAMMED SADHAKATHULLAH, AHAMMED HUSSAIN: Hierarchical PLA Platforms for Molecular Sensing, Biomimetic Interfaces, And Therapeutic Delivery
  
  Author: MADHANI MOHAMMED SADHAKATHULLAH, AHAMMED HUSSAIN
  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: 26/06/2025
  Reading date: 24/07/2025
  Reading time: 10:00
  Reading place: ESCOLA D'ENGINYERIA DE BARCELONA EST meet.google.com/jcj-gott-muw Edifici A. Aula A1.06 Planta 1 - https://eebe.upc.edu/ca/lescola/com-ar
  Thesis director: TORRAS COSTA, JUAN | ARMELIN DIGGROC, ELAINE APARECIDA
  Thesis abstract: At the intersection of materials science and biomedicine, this thesis explores the development of bioinspired and biodegradable polymeric systems capable of supporting lipid bilayers and enabling functional applications in biosensing and biomedical delivery. Conducted within the Marie Skłodowska-Curie Innovative Training Network BioInspireSensing, this research reflects a collaborative effort involving Universitat Politècnica de Catalunya (UPC) in Spain, the University of Teramo in Italy and the University of Warsaw in Poland.At the heart of this thesis lies the use of polylactic acid (PLA), a biocompatible and bioresorbable polymer, to develop two distinct yet complementary material platforms: nanostructures for biosensing and microparticles for therapeutic delivery. The first part of the work focuses on the fabrication of PLA nanomembranes and thin films, functionalized with PEG-cholesterol and bioactive peptides for sensing and to facilitate the stable immobilization of lipid bilayers. These biomimetic membrane systems were subsequently integrated into electrochemical sensors capable of detecting biologically relevant molecules—such as antioxidants and cholesterol—offering enzyme-free, biocompatible detection platforms with high sensitivity and selectivity.The second part of the thesis shifts focus to the design of PLA-based microparticles as delivery vehicles. Porous PLA microparticles functionalized with PEG-cholesterol were developed for the targeted and controlled release of therapeutic agents, including the anticancer drugs curcumin and tamoxifen. These systems were evaluated through in vitro studies to evaluate drug release profiles, confirm cytocompatibility, and examine the antitumor efficacy of the microparticles in model cancer cell lines. Taken together, these two material systems highlight the remarkable versatility of PLA as a foundation for building hierarchical, multifunctional biointerfaces. By connecting advances in molecular sensing, biomimetic membrane design, and therapeutic delivery, this work pushes forward the development of next-generation biodegradable materials with real potential in areas like implantable sensors, smart drug delivery systems, and bioelectronic devices. Beyond its technical contributions, the thesis reflects the collaborative and interdisciplinary spirit of the BioInspireSensing network—bringing together insights from materials science, molecular engineering, and biomedical research.
  

DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS

• HERNÁNDEZ BURGOS, SERGI: Development of Accelerated Fully Focused SAR Altimetry Algorithms
  
  Author: HERNÁNDEZ BURGOS, SERGI
  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: 30/06/2025
  Reading date: 24/07/2025
  Reading time: 11:00
  Reading place: Aula MERIT Dpt. TSC, D5-010, Campus Nord
  Thesis director: BROQUETAS IBARS, ANTONI | GIBERT GUTIÉRREZ, FERRAN
  Thesis abstract: The capability to measure ocean surface topography from space emerged in the 1970s with satellite radar altimeters. Since then, it has become essential in Earth observation, supporting a range of applications, from coastal water-level monitoring and sea-ice elevation, to quantifying sea level rise. Advances in radar altimetry have significantly improved the along-track resolution, progressing from kilometre scale in Low Resolution Modes to approximately 300 metres with Synthetic Aperture Radar (SAR) techniques using delay/Doppler processing, and even metre-scale resolution with Fully Focused SAR (FF-SAR). While Low Resolution and delay/Doppler algorithms are now operationally mature, FF-SAR algorithms remain relatively new and computationally demanding, limiting their operational use. This thesis introduces two novel algorithms designed to enhance the computational efficiency of FF-SAR radar altimetry processing, making it feasible for current and future satellite missions.The first alternative is a frequency based algorithm, named Omega-K Closed-Form algorithm, providing up to 4000 times of improvement in computational efficiency compared to the classic FF-SAR Back-projection algorithm. The algorithm is validated using data from point targets and open ocean. Additionally, the Omega-K algorithm is applied to estimate wavelength of long traveling ocean waves.The second alternative is an Accelerated Back-projection algorithm, which significantly reduces the computational runtime of classic Back-projection on a CPU-based architecture by a factor of 28, and a factor up to 13 on a GPU-based architecture. With respect to the classic Back-projection on a CPU, combining GPU processing with the Accelerated Back-projection achieves an overall computational improvement up to 1500. This method preserves accuracy and enables near-real-time processing, validated extensively with transponder and open ocean data. The Accelerated Back-projection algorithm is slower than the Omega-K algorithm, but it is more versatile, robust, accurate, and precise.Additionally, an alternative approach to delay/Doppler processing is introduced and extensively evaluated. This method, named Sub-looked Back-projection algorithm, is a variation of the classic Back-projection method. It generates waveforms with a resolution of 300 metres, comparable to those obtained from conventional delay/Doppler methods, but without relying on the typical approximations commonly employed by standard delay/Doppler processors to simplify computations. Furthermore, a comparison between delay/Doppler algorithms and the Sub-looked Back-projection method is conducted, assessing biases as a function of Significant Wave Height (SWH) in selected regions. Results indicate that the Sub-looked Back-projection method reduces SWH biases by 20% compared to conventional delay/Doppler processing. When implemented on GPU architectures, this method achieves processing speeds comparable to current operational delay/Doppler processors.Collectively, these methods represent a substantial step toward faster, as accurate as possible, and more versatile radar altimetry processing, paving the way for the next generation of operational satellite missions.
  
• MASANAS JIMÉNEZ, MIQUEL: Simple coherent technologies for next-generation edge optical networks
  
  Author: MASANAS JIMÉNEZ, MIQUEL
  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: 30/06/2025
  Reading date: 28/07/2025
  Reading time: 10:30
  Reading place: Aula Teleensenyament, Edifici B3 - Ricardo Valle Sala 103 Planta 1, Campus Nord UPC
  Thesis director: PRAT GOMA, JOSEP JOAN
  Thesis abstract: Optical fiber communications have revolutionized the telecommunications networks in all segments, leveraging a wide set of advantages ranging from THz capacity to low-loss, security and form factor. In long-haul and core networks, optical links use a plethora of properties of the electromagnetic field jointly to maximize the throughput of the deployed infrastructure, such as its frequency, phase, polarization and amplitude, enabled by coherent detection. In contrast, in access and fronthaul systems, cost-effectiveness has typically constrained the dimensions used for data transmission to amplitude and coarse frequency multiplexing, based on direct-detection. While both approaches have succeeded by optimizing link properties for their respective requirements, the growing traffic near the edge of the networks forecasts the need to implement the advantages of coherent detection and full field modulation, such as scalability, increased capacity and network flexibility, even in cost-constrained segments.This thesis aims to develop and assess architectures and technologies to simplify full-field modulation and coherent detection for edge segments like fixed access and mobile front-haul, especially over passive optical networks. In particular, single-sideband techniques of signals modulated over electric carriers are used to achieve single-laser transceivers and spectrally efficient sub-carrier multiplexing with increased sensitivities and avoiding relevant link setbacks such as Rayleigh backscattering. To further reduce the cost and consumption of the systems, analog processing for the phase-noise compensation is included, and the links’ performances are evaluated. The thesis focuses on low-cost and footprint devices, suitable for urban and local access networks, such as fiber to the home, business, antenna, etc. using a wavelength-to-the-user/antenna approach, to deliver the highest sensitivity and spectral efficiency possible with the lowest expression of coherent detection and transmitter complexity. Therefore, the main topics discussed in the thesis are simplified coherent detection and field modulation, phase noise cancelling, coherent passive optical networks power budget, scalability and spectral efficiency, and single-sideband techniques as a key-enabling tool for the accomplishments of the aforementioned targets.
  

DOCTORAL DEGREE IN SUSTAINABILITY

• EL MADAFRI BENNIS, ISMAIL: Confounding Factors-Aware Hierarchical Deep Learning for Sustainable Edge Wildfire Detection
  
  Author: EL MADAFRI BENNIS, ISMAIL
  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: Article-based thesis
  Deposit date: 20/05/2025
  Reading date: 24/07/2025
  Reading time: 12:00
  Reading place: DECA - D1-103
  Thesis director: PEÑA CARRERA, MARTA | OLMEDO TORRE, NOELIA
  Thesis abstract: Wildfires present a significant threat to ecosystems, property, and human life, underscoring the need for accurate, adaptable, and efficient detection systems. This thesis introduces a novel approach to wildfire detection that addresses key limitations in accuracy, adaptability, and sustainability, emphasizing real-world deployment and resource-conscious design. Through three interconnected studies, the research develops a structured, confounding factors-aware framework that progresses from dataset creation to efficient, real-time deployment solutions.The first study establishes a confounding factor-aware wildfire dataset and a multi-task learning framework to address false positives caused by challenging elements, such as clouds, fog, and reflections. By training models on both fire classification and confounding element identification, this approach significantly reduces false alarms, enhancing model precision in complex detection scenarios. The second study advances this framework by incorporating a hierarchical domain-adaptive learning approach that integrates forest-specific and non-forest datasets. This dual-dataset strategy, with shared and specialized layers, enhances the model’s ability to generalize across diverse environmental conditions, providing a more adaptable solution for varied forest contexts.Building on these foundations, the third study introduces knowledge distillation to transfer insights from a complex, hierarchically trained model to a lightweight model optimized for edge devices, such as drones. This approach maintains high detection accuracy while minimizing computational demands, supporting sustainable deployment. A novel metric, the Confounding Element Specificity (CES), is also introduced to evaluate the model’s ability to handle confounding elements in real-world settings, contributing to efficient resource deployment and accurate monitoring.Together, these studies propose a structured, scalable framework for wildfire detection that combines technical rigor with practical, sustainability-focused applications. The findings contribute adaptable, high-accuracy models intended for real-world implementation and offer a foundation for further research in sustainable, AI-driven environmental monitoring and wildfire management.
  

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.