Committee:
     PRESIDENT: CHOWDHURY, KAUSHIK ROY
     SECRETARI: ABADAL CAVALLÉ, SERGI
     VOCAL: DINI, PAOLO
Thesis abstract: In today's landscape, data are increasingly becoming an invaluable resource to enhance decision-making, enable predictive insights, improving operational efficiency, among numerous other applications. Within the current data-centric mindset, wireless sensors play a facilitator role, allowing the collection of data in a flexible, low-cost, and simple-to-deploy way.One of the ever-pending challenges of wireless sensor node technologies is their limited energy availability, particularly their limited battery life. To extend their battery life, sensor nodes need to use their energy as frugally as possible. The optimal behavior for a sensor node is highly dependent on the varying operation conditions. Thus, to operate optimally, sensor nodes need to incorporate adaptive mechanisms to dynamically adjust their behavior at runtime. These adaptive mechanisms are commonly referred to as Dynamic Energy Management (DEM).Despite the progress made in DEM, commercial sensor nodes continue to mostly operate using static behaviors, wasting energy. The main limitation impeding the widespread adoption of DEM is that it renders the node's behavior dependent on the operating conditions, thereby making the node's behavior unpredictable. In recent years, self-awareness has been proposed as a promising solution to this challenge. Self-aware systems autonomously adjust their behavior at runtime based on their internal and external operating conditions to achieve their operational goals as efficiently as possible. Consequently, while the behavior of a self-aware system may not be known at a given time, these systems provide some level of predictability by complying with their operational goals.This thesis delves into the use of self-awareness at the sensor node level to guide the node's adaptive behavior. The main objective of this thesis is to provide a solid foundation to support future progress in self-aware sensor nodes. In pursuit of this goal, it presents a reference architecture of a self-aware sensor node solving the existing lack of standardization in their design. Additionally, it proposes two self-aware monitoring methods enabling the node to comply with its battery lifetime target while optimizing its energy allocation to maximize its monitoring accuracy. Another key aspect that limits the adoption of self-awareness at the sensor node level is the node's lack of information and computing capabilities to model complex environments, as is usually the case in Structural Health Monitoring (SHM) applications. This thesis tackles this issue by proposing an anomaly-aware monitoring method tailored for SHM applications, which models the local vibration patterns measured by the node to determine the current monitoring requirements for the node. Finally, the thesis ends by exploring how the concept of self-awareness can be extended through the network, enabling the interaction between self-aware sensor nodes and a self-managing monitoring application running in the cloud.

Committee:
     PRESIDENT: TRILLA ROMERO, LLUÍS
     SECRETARI: BORDONAU FARRERONS, JOSE
     VOCAL: BARAIA-ETXABURU ZUBIAURRE, IGOR
Thesis abstract: This thesis presents an exploration into the field of advanced battery charger design and control, addressing critical needs across a spectrum of modern applications. It first outlines the increasing importance of battery chargers in various domains, emphasizing the requirements of efficiency, adaptability, and reliability. A detailed review of existing technologies and control strategies underscores the urgent need for innovation in charger design.The focus of this research is the design and development of a battery charger topology. This topology is based on cascaded multilevel converters that provide bidirectional power flow and galvanic isolation. It addresses the charging requirements of multiple batteries connected in series and incorporates two distinct dc links. The charger develops from a three-level configuration to a four-level configuration, finally leading to a generalized n-level charger.Integral to this work is the formulation of comprehensive linear models, from state-space to s-domain representations, which highlight the charger's complex dynamics. This allows for an in-depth understanding of its operational behavior and control characteristics.The thesis also introduces a well-tuned control system that synchronizes the operation of the two multilevel converters. This ensures optimal operation of the charger. The ac-dc converter regulates the dc link voltage and grid power factor, while the dc-dc converter regulates the shared dc link voltage and battery bank charging currents. The user has the flexibility to determine which converter controls the dc-link voltage regulation.A key innovation is the independent charge control for each battery bank. This feature allows batteries to reach full charge independently, regardless of their initial state of charge or rated capacity. This improves overall efficiency and battery management.In addition, the thesis provides a practical and straightforward design methodology for compensators based on the charger's linear schemes. It employs uncompensated gain loops and uses Bode plots for effective tuning of compensator parameters.Finally, the thesis outlines future research directions. These include experimental validation, exploring vehicle-to-grid integration, exploring nonlinear control systems, assessing off-board charger viability, examining renewable energy integration, enhancing grid-supporting features, evaluating scalability and efficiency, and evaluating real-world applications. Together, these efforts promise to advance and optimize the proposed battery charger, placing it as a central element in the field of efficient and sustainable energy systems.

Committee:
     PRESIDENT: PÉREZ RODRÍGUEZ, ALEJANDRO
     SECRETARI: VOZ SANCHEZ, CRISTOBAL
     VOCAL: HOYE, ROBERT LIANQI ZHAO
Thesis abstract: Chalcogenide materials have been central to some of the most significant events in the history of photovoltaic energy, includingthe fabrication of the first solar cell in 1883 by Charles Fritts, which was based on selenium. However, the rapid development ofcrystalline silicon starting in 1954, and the lack of knowledge on their most attractive properties, led to various chalcogenidebasedmaterials to being largely overlooked despite the technological efforts to advance solar energy from the 1960s onward.Only in the last 10 to 20 years have these materials garnered renewed interest in the scientific community, driven by newadvances in structure simulation and advanced characterization techniques in materials science.In particular, antimony and bismuth chalcogenides have garnered considerable interest, as they are constituted by earthabundantelements, which can be easily extracted from the refinement of natural ores. Also, they are mostly harmless to thehuman health and the environment, they exhibit optimal properties for photovoltaic technology (such as a high absorptioncoefficient and bandgap in the visible spectrum range), and their optical properties can be tuned through doping strategies,chemical substitution or solid solution fabrication. They also exhibit structural and electronic characteristics similar to other highperformancephotovoltaic compounds (e.g., hybrid perovskites), and their quasi-1D crystalline structure based on covalentlybonded ribbons linked by Van der Waals interactions leads to unique anisotropic properties, such as enhanced electronictransport in the direction of the covalent chains. Therefore, by adjusting the structure, crystalline orientation, and composition, it ispossible to develop new materials with a clear potential for next-generation photovoltaic technologies. Furthermore, their highabsorption coefficient and adjustable bandgap open the door to exploring new application avenues, such as flexible, semitransparentsolar cells, or compatible devices with the Internet of Things.In the context of this effort directed towards the development of chalcogenide compounds for photovoltaics, this thesis focuses onthree groups of chalcogenide and chalcohalide materials (i.e., including chalcogenide and/or halide anions), which exhibit thefollowing common features: they present properties analogous to hybrid perovskites – either structurally or electronically –, havea low-dimensional crystalline structure, are composed of abundant elements without toxicity risk, and they have been scarcelystudied, leaving many unanswered questions regarding their chemical nature, behavior as semiconductors, and performance inphotovoltaic prototypes.The work has several objectives. First, we study the effects of synthesizing Sb2Se3 under non-stoichiometric conditions, as wellas adjusting its optical properties by incorporating bismuth via thermal evaporation processes. Secondly, we develop aninnovative and versatile methodology for the fabrication of antimony chalcohalides (SbSeI and SbSeBr), based on a combinationof co-evaporation and high-temperature and high-pressure annealing, which enables the fabrication of a wide range ofcompounds that could not be effectively synthesized with the previous techniques. Finally, we investigate a new solutionprocessing methodology based on molecular precursor ink deposition which allows obtaining chalcohalide anti-perovskites(Ag3SBr and Ag3SI) at very low temperatures, opening the door for these compounds to also be manufactured using adaptableand low-cost chemical techniques. All materials have been studied using structural and optoelectronic characterizationtechniques, showing their potential as photovoltaic absorbers, and demonstrating that chalcogenides still have much to offer inthe field of solar energy.

Committee:
     PRESIDENT: CABOT CODINA, ANDREU
     SECRETARI: RAMOS CASTRO, JUAN JOSE
     VOCAL: PLATIKANOV, STEFAN
Thesis abstract: In this work, different nano, sub-micron, and microparticle materials have been embedded in various types of electrolytes, including ionic liquid gel polymer electrolytes (ILGPEs) and sodium chloride (NaCl), toenhance the performance of the filler-free fabricated capacitive devices for energy and sensing applications. The integration of these particles relies on their properties and beneficial role in devices for energy andsensing applications. In the energy field, this thesis explores the effect of incorporating SiO2 and Si@C sub-micron and nanoparticles into an ILGPE to enhance its energy storage capability. This work highlights the integration of these nanoparticles to improve the physicochemical characteristics of an ILGPE and, hence, its electrical performance, aiming to address the characteristic limitations of liquid electrolytes, such as leakage, or of GPEs, such as restricted ion conduction or high crystallinity. The composite ILGPEs exhibited capacitance improvements of 71% and 42%, for SiO2 and Si@C CGPEs, respectively, thereby demonstrating the beneficial role of these composites. Regarding the sensing field, this thesis explores two novel layers incorporating SiO2 particles into humidity and proximity sensing applications. Firstly, the viability of an ILGPE as a humidity-sensitive layer is assessed, and then different combinations of SiO2 nanoparticles and polyvinylpyrrolidone (PVP) are embedded into the ILGPE to enhance its humidity-sensing performance through increased sensitivity and reduced hysteresis. The results show that the SiO2 filler-ILGPEs achieve higher sensitivities and lower hysteresis. Secondly, a proximity sensor is developed using a dielectric layer formed from a mixture of SiO2 particles and NaCl. The fabricated proximity sensor has revealed a maximum capacitance sensitivity of 47.4 cm-1 and an operation range of 2-14 cm. Both layers exhibit effective potential for sensing applications and leverage the benefits of using environmentally friendly and cost-effective materials.Finally, in this thesis, a new surface modification of a polytetrafluoroethylene (PTFE) layer has been investigated, which allows for change from hydrophilic and hydrophobic characteristics. The proposedmethod can be helpful to optimize the electrospray deposition technique for particle coatings. This study contributes to enabling technology by improving the deposition processes and enhancing the coatings'functionality in energy storage and sensor applications. Summarising, this thesis has suggested the use of SiO2 nanoparticles as a good alternative for tailoringelectrolyte properties, defined a starting point in the use of SiO2 nanoparticles as a proximity-sensitive layer, and revealed novel CILGPEs that can be integrated into humidity sensing and energy

Committee:
     PRESIDENT: VOZ SANCHEZ, CRISTOBAL
     SECRETARI: GARIN ESCRIVA, MOISES
     VOCAL: HERNÁNDEZ GARCÍA, DAVID
Thesis abstract: This thesis works towards efficient and cost-effective methods to improve the performance of thin silicon solar cells. Focusing on two principal objectives, the Thesis develops novel techniques to enhance the production of colloidal crystals and the possibility to apply these crystals to improve the light trapping efficiency, as well as creating a unique structure for lased doped solar cells. Both advancements focus on improving the production solar cells using low-temperature processes and thin wafers, thus circumventing the dependences of high temperature procedures, while bolstering light trapping capabilities. This approach is motivated by the restarting trend to reduce silicon wafer thickness, therefore this work is pushed by the need to overcome the actual technical and physical constrains. The initial part of the Thesis focuses on the implementation of an electrospray system for the creation of colloidal crystals. These colloidal crystals are intended for application as photonic light trapping structures in solar cells. Afterwards, these structures are tested within a laser firing process to double check the viability to be used within the laser firing technique commonly used in solar cell fabrication.The main achievements within the electrospray deposition technique are the development of polystyrene and SiO2 colloidal crystals with areas in the range of 1-2cm2 and up to 17 layers of ordered particles while keep good optical quality. These layers are created at room temperature and with a process that could be adapted to batch processing and parallelized to increase the area. The technique has also been adapted to be used in non-even surfaces like C-Si pyramids or black silicon. At the same time, these structures had been used to create inverse colloidal crystals from Al2O3 and Al2O3 /TiO2 shells while getting rid of polystyrene nanoparticles. The final Al2O3 /TiO2 structure obtains high reflectivity values up to 98.2%. Finally, these inverse opals are created on top of Al2O3 passivated C-Si wafers. These structures are able to withstand a laser firing process while keeping the passivation, demonstrating the capability to be used with in the solar cells fabrication process.The second part of the thesis focuses in the creation of a process to achieve low temperature solar cells by means of highly-doped regions that are punctually defined through laser processed dielectric films. This technique call “DopLaCell” stand for doped by laser solar cell. In the initial stages of the process and as a proof of concept, 1x1 cm2 solar cells were created on both p- and n-type substrates with efficiencies of 11.6% and 12.8% respectively. In a second step, 1x1 cm2 n-type c-Si solar cells are created using the “cold” p+ emitters used in the “DopLaCell” structure. This second batch of solar cells uses a Heterojunction with Intrinsic Thin layer (HIT) in the front face. This approach avoids the use of Transparent Conductive Oxide (TCO) on the back side of the cell thus improving the reflectivity especially with IR photons. These cells reach efficiencies up to 18.1%. Finally the process is being improved towards a pure texturized “DopLaCell”. In this final step, totally “cold” 2x2 cm2 solar cells are fabricated with and efficiency up to 17.0 % .This work represents a one big step forward towards a future path of thin silicon solar cells fabrication, addressing the actual technology limitations and enabling the possibility to overcome the principal issues. This research lays the ground towards thin, affordable and efficient solar cells improving the path towards a more viable and eco-friendly energy future

Committee:
     PRESIDENT: GARCERÁ SANFELIU, GABRIEL
     SECRETARI: GARCIA DE VICUÑA MUÑOZ DE LA NAVA, JOSE LUIS
     VOCAL: FIGUERES AMORÓS, EMILIO
Thesis abstract: This PhD thesis examines various reactive current injection techniques and strategies to address the challenges associated with power grid management during abnormal conditions. The aim is to offer new perspectives and practical solutions to improve the operation and reliability of the power system. To this end, three contributions are presented. The first contribution focuses on a new control approach for reactive current injection in distributed generation systems. The method proposes a method of independent reactive current injection for each phase, which optimises the system's ability to handle load imbalances and fault events. In addition, peak current control is incorporated to protect inverters, ensuring safe and efficient performance. The second contribution focuses on improving voltage support in isolated microgrids during short-circuit events. An innovative strategy is introduced that uses electric vehicles to provide voltage support by injecting active power, instead of conventional reactive injections. This approach not only improves system stability during disturbances, but also avoids unwanted overvoltages through coordinated control between distributed generators and electric vehicles. The third contribution proposes a control scheme for the remote elimination of voltage unbalance in grid-connected inverters. This approach uses the virtual grid concept to compensate negative sequence voltage at remote points of the power system. In addition, it integrates peak current control to protect inverters and ensure optimal performance with low control data traffic. To summarise, these contributions address various aspects of the operation and control of distributed generation systems and microgrids, including reactive current injection and voltage unbalance compensation. They provide innovative and efficient solutions to enhance grid stability and security.

Committee:
     PRESIDENT: LEIJA SALAS, LORENZO
     SECRETARI: ALVARADO SERRANO, CARLOS
     VOCAL: GUTIERREZ SALGADO, JUAN MANUEL
Thesis abstract: Chronic kidney disease is considered a risk factor for the development of cardiovascular disease because it is one of the main complications of diabetes mellitus and arterial hypertension, which are themselves considered cardiovascular risk factors. Therefore, it is important to periodically evaluate renal function in at-risk groups, such as diabetic and hypertensive patients or those with cardiovascular disease. In this doctoral thesis, six parameters of ECG ventricular activity are proposed to assess the progression of renal damage in diabetic subjects, with and without hypertension and hemodialysis treatment.To obtain ECG recordings from subjects and patients, a low-power, long-duration ambulatory monitor was developed for the simultaneous acquisition of three ECG leads. This monitor incorporates an algorithm that uses the continuous wavelet transform (CWT) to measure heart rate beat-by-beat in real-time. It has a CMRR greater than 80 dB at 60 Hz, a bandwidth of 0 to 150 Hz, a sampling rate of 1 kHz, and a current consumption of 50 mA, resulting in an average battery life of 84 hours. The monitor also detects false electrode contacts, stores data on a microSD memory card, and includes a user interface that facilitates interaction with the device.Specific PC software was developed for reading, storing, visualizing, and analyzing ECG records, as well as managing the patient's personal information. A SQL Server database was implemented to manage the records, corresponding analysis results, and patient data. The software uses Microsoft Excel files for the exchange of input and output information, with formats that are easy to create and interpret in other software development applications. The software algorithms employ CWT and are robust against the presence of noise, artifacts, and baseline drifts in the recording. These algorithms include detection and classification of T waves and QRS complexes, adaptation to changes in heart rate, and interval calculation. The algorithms work with CWT using B-spline basis functions, allowing them to handle any integer scale and ensuring that the analysis is not restricted to scales that are powers of two. The software enables the analysis of ECG recordings with different sampling rates by automatically selecting the CWT scale.The QRS complex detector, evaluated with the MIT-BIH, ST-T, and QT databases, achieved excellent performance with a sensitivity and positive predictivity of 99% from a total of 986,467 QRS complexes analyzed. For the QRS complex and T-wave characteristic point delineator, evaluated with the CSE, PTB, and QT databases, the errors at the Qi, J, and Te points were within the tolerance limits for deviations with respect to the manual measurements by CSE experts. For the Tp point, compared to another similar algorithm, the deviation was 1 sample (4 ms). According to these results, the developed algorithms allow reliable measurement of ECG ventricular activity intervals.For the analysis of the progression of renal damage in diabetic patients with and without hypertension and hemodialysis treatment, ECG records from the following databases of diabetic patients were used: GE-71, GE-75, and HR-48H. To analyze the five stages of diabetic nephropathy, three groups of diabetic patient records were created from the above databases: 39 patients without hypertension and without hemodialysis (DSH_SH), 22 patients with hypertension and without hemodialysis (DH_SH), and 20 patients with hypertension and hemodialysis (DH_CH). The proposed parameters representing ECG ventricular activity and heart rate are: the intervals (QpTe)c, (RTp)c, and (SpTp)c, and the ratios TpQp/RR, TpSp/RR, and RTe/TeR, which relate to two consecutive beats of the cardiac cycle. These parameters cover the five stages of diabetic nephropathy and enable the evaluation of the progression of renal damage in diabetic patients with and without hypertension and hemodialysis.

Committee:
     PRESIDENT: ASENSI LÓPEZ, JOSÉ MIGUEL
     SECRETARI: PLACIDI, MARCEL JOSE
     VOCAL: RIERA LORENTE, SERGI
Thesis abstract: Silicon is abundant in nature and plays a predominant role in the photovoltaic industry for generating electrical energy. However, the current cost of this solar technology remains high, especially at a commercial level where efficiency reaches 22%. One strategy to reduce the cost of solar energy production involves enhancing the efficiency of solar modules. This can be achieved by integrating new techniques and technologies into the manufacturing processes of the industry, along with the use of abundant and low-toxic materials.Multi-junction solar cells (tandem) enable the integration of two different technologies to leverage their respective qualities as light absorbers, thereby enhancing their electrical performance. Additionally, these cells facilitate the simplification and adoption of new techniques during the manufacturing process. With its Band Gap of 1.1eV, silicon stands out as an excellent candidate for the bottom cell in multijunction or tandem solar cells.The objective of this thesis is to enhance the efficiency of silicon solar cells by utilizing them as multijunction bottom cells to create tandem solar cells. This will be achieved by incorporating a front solar cell based on emerging technologies.To achieve this objective, the introduction is developed, which includes a brief state-of-the-art overview of silicon-based solar cells, the development of tandem solar cells, and the most promising alternatives for emerging inorganic absorbers with adjustable Band Gap, such as kesterites or chalcopyrites (e.g., CuGaSe). The theoretical analysis enables the selection of technologies and processes developed in available laboratories.The application of robust methods for depositing selective contacts in silicon is under investigation. This process aims to prepare the silicon for the thermal and chemical processes involved in the growth of inorganic solar cells, such as kesterites or CGS. This approach enables the development of a robust, efficient, and long-term multijunction solar cell.In a second section, the study on semi-transparent selective contacts for solar cells with inorganic absorbers, such as kesterites or CGS, is presented. The goal is to obtain a compatible substrate for tandem solar cells. As an alternative to traditional CdS for the ETL, we propose the use of Al2O3/TiO2/Mg,i:ZnO layers. Additionally, the potential of enhancing its characteristics by adding polymers (PEI, Glycine) as dipoles is studied.Regarding the hole transport layer (HTL), a semi-transparent alternative to the opaque MoSe2 layers was developed using V2Ox.This layer functions as an interface between the absorber and the transparent electrode (TCO). The incorporation of this layer into kesterite solar cells yielded a semi-transparent device with promising haracteristics, and its application has a significant impact on the efficiency of solar cells.In the last section, a manufacturing process for tandem solar cells is proposed, utilizing Silicon technology as the bottom cell and emerging inorganic solar cells, such as kesterite and CGS, as the top solar cell. Strategies are studied to create a monolithic two-terminal (2T) device, with attention to preserving the physical and electrical characteristics of each device throughout the manufacturing process and during chemical and thermal exposures. Additionally, a study is presented on strategies for the formation of a monolithic device with three interdigitated back contact (IBC) type terminals, which is crucial for obtaining efficient and stable devices in the long term.Through the implementation of these techniques, we anticipate contributing to the research and development of tandem solar cells based on abundant and sustainable materials. This advancement could significantly accelerate the global adoption of solar energy as a clean and renewable source.

Committee:
     PRESIDENT: JIMÉNEZ JIMÉNEZ, DAVID
     SECRETARI: ABADAL CAVALLÉ, SERGI
     VOCAL: CUCU LAURENCIO, NICOLETA
Thesis abstract: Lately, in the rise of the era of 2D materials, Graphene is one of the materials that has been extensively investigated for its possible integration in computing devices and thus computing circuits. This is mainly attributed to its very wide set of appealing properties. The combination of its electronic properties with others, such as mechanical, optical or chemical properties, can extend the range of use of computing devices and lead to groundbreaking interdisciplinary applications. However, this integration of Graphene in switching and computing elements is not easy. In this dissertation, the Non-Equilibrium Green's Function method (NEGF), along with the Tight Binding Hamiltonians, are fitted on experimental data from fabricated Graphene devices. Although as a computational method, NEGF is appropriate for the simulation of small-scale devices in the regime of nanometers, its ability to be efficiently expanded for the description of larger devices is presented. The aforementioned electronic properties of the material are highly related to its shape and structure. Consequently, it requires a very precise fabrication method that can guarantee the minimum presence of defects on the Graphene grid. For that reason, the effect of defects is deeply investigated. The NEGF method is further enhanced in order to be able to incorporate lattice defects. The most common lattice defects are included, meaning the single and double vacancy. A framework has thus been created, so that for the first time the user can select areas of interest on the grid, in which the defects will be concentrated. Those concentrations can also be variable. Moreover, an extensive study is conducted on defective grids with different concentrations of single and double vacancies. The investigated grids are non-rectangular and have regions with different widths. The effect of those vacancies on the electronic properties of Graphene is investigated, and more specifically their effect on the conductance and the energy gap of the device, as well as the effect on circuit-centered characteristics such as the leakage current and ON/OFF current ratio. Having a functional, robust, versatile, and accurate model, the focus of this thesis is extended to the level of circuits. The model is imported into SPICE through Verilog-A. In this part, the thesis emphasizes on the investigation of the switching capabilities of L-shaped Graphene Nanoribbons (GNRs). These structures have been proven to be able to operate as switches, without the use of a back gate, and here, the properties that are dependent on their dimensions are explored and optimized for the first time. The optimized structures are then used for the realization of a set of computing topologies. Initially, a novel area-optimized 2-branch comb-shaped topology is introduced for the realization of a universal computing set that consists of an AND, OR, NOT gate, and a Buffer. All these logic operations can be mapped on the same topology through appropriate biasing. Then, an extension of this, the 3-branch comb-shaped topology is proposed, which is able to operate as a 2-XOR, 3-XOR and 3-MAJ gate. The circuit of a 1-bit full adder, is also presented. For the evaluation of the performance of the topologies, several related metrics are employed such as the area, delay, power dissipation and the power-delay product. The operation of these topologies relies of the principles of Pass Transistor Logic (PTL) and reconfigurable computing. Finally, in an attempt to go beyond the conventional Boolean logic, the compliance of Graphene with Multi-Valued Logic (MVL) circuits and applications is investigated. The ability of a Graphene Quantum Point Contact (G-QPC) device to encode the digits of the radix-4 numeral system is presented and as a proof of concept, the operation of an arbitrary radix-4 adder is explained.

Committee:
     PRESIDENT: DUEÑAS, SALVADOR
     SECRETARI: JEHL, ZACHARIE VICTOR SAMUEL NATHANAEL
     VOCAL: CAMPOY QUILES, MARIANO
Thesis abstract: A solar cell consists in an absorber material that transforms light into excited charge carriers, and carrier selective contacts that allow the flow of the carriers {electrons/ holes) only in a particular direction. In this work different materials that can be used as carrier selective contacts have been studied and characterized by means of methodologies used in c-Si solar cells to understand their operation principles. The exploration of these novel materials resolves around the need of solving multiple problems of current technologies. These include the difficulty in generating ohmic contacts due to interface effects such as Fermi Level Pinning {FLP) in n type c-Si as well as the use of hazardous dopants in high temperature steps to fabricate Silicon solar cells. Finally, the knowledge on the deposited materials has been used in other technologies to prove their application extends beyond crystalline Silicon.

Committee:
     PRESIDENT: ITUERO HERRERO, PABLO
     SECRETARI: MORENO AROSTEGUI, JUAN MANUEL
     VOCAL: MARGARIT TAULÉ, JOSEP MARIA
Thesis abstract: This thesis contributes to the field of neuromorphic hardware. In particular, to the significant improvement of a scalable hardware architecture, named Hardware Emulator of Evolvable Neural Spiking Systems (HEENS), for the real-time execution of spiking neural networks (SNNs) in cognitive applications. SNNs are neural networks inspired by the biological activity of the brain, designed to process discrete temporal events, offering improved capabilities for handling temporal data as well as local plasticity, thus exhibiting greater energy efficiency compared to traditional neural networks.The HEENS architecture is implemented on several AMD (Xilinx) Zynq hardware platforms, which combine ARM processing cores with programmable logic (FPGAs), known for their high flexibility and parallelism in the execution of different neural models. One of the key achievements of this thesis is the optimization of the architecture to reduce latency, minimize resource usage, increase processing capacity, overcome previous architectural issues, and improve adaptability to various cognitive applications, such as sensory processing and pattern recognition.The results obtained can be divided into architectural contributions and experimental results in real applications. In the first part, this work improves the synaptic mapping capability, develops new system configuration mechanisms, and introduces interaction with external sensors.The enhanced system integrates an HDMI interface, demonstrating real-time visualization of neural activity and the neural and synaptic parameters of the SNN allows continuous monitoring without affecting system performance. This real-time monitoring capability has been tested in multiple experiments, where a precise representation of neural activity was observed on a 1 ms time scale, considered to be real-time, with support to other time scales, both faster or slower. The use of HEENS in physical sensor processing is highlighted, where it was proven that the architecture can adapt in real-time to changes in input signals, making it an ideal platform for applications in robotics and autonomous systems.Regarding testbenches and applications, significant results are presented in the implementation of cognitive applications using HEENS. In handwritten digit recognition, the architecture showed high accuracy using SNN models with synaptic plasticity, achieving good performance in terms of processing time and energy consumption compared to other existing solutions. Another key result is the hardware emulation of neuronal cultures, comparing the behavior of simulated neural networks in vitro, in silico, and in duris silico (physical hardware). The experiments showed that HEENS is capable of faithfully replicating the behavior and statistical properties observed in real neuronal cultures, opening new possibilities for research in neuroscience and biomedicine.Finally, the thesis concludes that the HEENS architecture not only offers a flexible and efficient environment for the research and development of SNN but also enables its implementation in real-world applications demanding real-time processing with good energy performance. The advances achieved in this work represent an important step toward the creation of next-generation scalable neuromorphic systems capable of efficiently emulating complex cognitive functions.