Physics
Photovoltaics are a key technology in the transition toward renewable energy. Among emerging materials, poly(3-hexylthiophene) (P3HT) offers an attractive alternative to silicon owing to its solution processability, mechanical flexibility, and tunable optoelectronic properties. This thesis investigates how electric fields, mechanical deformation, and processing conditions influence the structural and photophysical properties of P3HT and the flexible substrate poly(ethylene terephthalate) (PET) using complementary time and frequency domain spectroscopic techniques. Femtosecond transient absorption pump-probe spectroscopy demonstrates that below-band-gap excitation directly generates polaron pairs (PPs) in P3HT. The transient response comprises fast PP and slower delocalized polaron pair (DPP) contributions. External electric fields modify the competition between DPP recombination and bimolecular annihilation, while uniaxial stretching up to 7% redistributes PP and DPP populations through polymer chain alignment. Above this strain, the transient response becomes increasingly complex owing to efficient strain transfer and microcrack formation. Raman and ultraviolet–visible spectroscopy correlate mechanical deformation with structural and optical changes. P3HT and PEDOT:PSS/P3HT films retain an essentially constant optical band gap up to approximately 7% strain, followed by a slight widening at 10%, indicating the onset of electronically significant deformation. Analysis of the Raman C=C and C–C stretching modes shows that variations in band position and full width at half maximum distinguish temperature-induced morphological changes from mechanically induced chain alignment. PET exhibits increased optical absorption and irreversible Raman spectral changes above approximately 5% strain, indicating molecular reorganization.
Understanding how collective patterns emerge on graphs is a fundamental challenge across disciplines, from biological and ecological networks to computational and physical systems. This thesis explores the interplay between network topology and emergent dynamics using minimal models and spectral graph techniques.
A first investigation focuses on network inference, showing that Turing patterns encode structural information about the underlying graph, which we use to infer missing links. The second study investigates multistability in reaction-diffusion networks, showing how local spectral gaps influence the attractor landscape of Turing patterns using a heuristic binary classification algorithm. Finally, the third study applies the sandpile model to soil erosion processes, bridging concepts from self-organised criticality and connectivity-based geomorphology to investigate the role of minimal models in empirical research.
This thesis combines theoretical analysis, computational modelling and empirical validation to highlight how structure shapes dynamics across different contexts and illustrate the potential of minimal models as predictive, explanatory and exploratory tools for complex systems.
The relationship between network structure (structural connectivity, SC) and network representations of dynamics (functional connectivity, FC) is a topic of high scientific interest both for advancing theoretical understanding of complex systems and for its relevance to a wide range of applications.
In this thesis, correlations between structural and functional connectivity were investigated distinguishing between synchronous and sequential activity of the nodes. The primary analysis encompasses applying different dynamical models to network architectures to explore how SC/FC correlations are shaped by variations in network topology, coupling strength, and intrinsic system parameters across excitable, chaotic, and oscillatory dynamics. A more detailed investigation was conducted on regular graphs of coupled logistic maps. Symbolic encoding of the initial dynamics was used to construct equivalent cellular automaton models, followed by an analysis of the structure of their resulting attractors. The influence of noise on SC/FC correlations was also explored. Finally, SC and the two types of FC were conceptualized in a hydrological case study. Structural and functional networks were constructed from data collected in the Walnut Gulch Experimental Watershed (Arizona, USA). SC/FC correlations served as metrics to describe event-level hydrological responses of the watershed after various rainfall events, and their relationships to hydrological quantities were analyzed.
Photosynthesis is an essential process through which sunlight is converted into chemical energy, sustaining virtually all life on Earth. In the specific case of oxygenic photosynthesis, Photosystem II (PSII) plays a pivotal role as a major component of the photosynthetic machinery, responsible for the initial light absorption and generating molecular oxygen. This process involves numerous protein-pigment complexes within PSII. The photosynthetic apparatus is rich in colored pigments, which not only make it visually appealing but also crucial for capturing and transporting sunlight through excitation energy transfer. Due to the large size of these proteins and the electronic complexity of the pigment molecules embedded in the membrane, multiscale quantum-classical methods are essential for studying the processes. The protein environment significantly influences the tuning of the excitation energy of the pigments, thereby establishing an energy funnel in such systems. This thesis aims to deepen our understanding of the lightharvesting process in the antenna complexes of PSII. To achieve this, a multiscale approach is employed. This involves using the density functional tight-binding (DFTB) method to perform ground state molecular dynamics within a quantum mechanics/molecular mechanics (QM/MM) framework, coupled to an electrostatic classical environment. Following this, the time-dependent extension of the long-range-corrected DFTB is applied to obtain the excitation energies of each pigment molecule, within a QM/MM setting. This method generates essential excitonic parameters such as site energies, couplings, and spectral densities, which are utilized to model the spectroscopic properties. Furthermore, the calculated results have been compared with experimental data, showing great agreement for the antenna complexes in PSII. This alignment ensures the robustness of the methods, validating their use for studying light harvesting in both plant and cyanobacterial systems.
In this thesis, we discuss the properties of quantum antiferromagnetic spin chains with long-range (LR) tunable interactions and positional disorder. By long-range, we mean that the range of interactions falls-off as a power law with the distance. We mainly focus on the entanglement properties of these systems and consider both ground state and high-energy eigenstates.
Additionally, the dynamical properties of the LR random spin chain are considered by investigating the post-quench entanglement growth as a function of time. Finally, we study the response of this system to a local perturbation by considering the quantum fidelity variations with system size.
While analytical results for LR interacting disordered systems are not abundant in the literature, we achieve the implementation of strong disorder renormalization group(SDRG) procedures (and variants) on such models. We systematically confront our results with numerical exact diagonalization(ED) to confirm the obtained predictions.
The contribution of the chemical enhancement mechanism to the SERS process has been studied using a Kretschmann configuration (KC) with a thin silver layer attached to the totally reflecting surface for reproducibility of the results. After studying fundamental properties, additionally, the KC was applied for specific applications.
The basic KC setup has been optimized and the observed enhancement was investigated in detail. SERS studies have been performed on a monolayer of Nile blue, Crystal Violet, and 4-Nitrobenzenethiol. Under resonance conditions for the coupling of the light to the surface plasmons, a decay of the Raman line intensities has been observed over time, converging to constant signal levels. By analyzing this time-dependent intensity variation for the single vibrational modes, we found a mode-dependent Raman deactivation rate. This process has also been investigated for different angles of incidence of the beam (varying the resonance condition), and a clear dependence on the strength of the coupling to the plasmons for the behavior of the different Raman lines has been found. Although, a uniform enhancement of the electromagnetic fields of exciting and scattered light can be assumed for a given angle of incidence when considering the electromagnetic enhancement (EME) mechanism, which usually dominates the SERS process, the relative enhancements were found to be strongly mode-dependent, which is a clear indication of an electronic effect. Obviously, the KC allows for the observation of a dominating chemical enhancement (CE) in these single-layer SERS experiments.
Knowing that only chemisorbed molecules should contribute to the CE, we switched this mechanism off by introducing an isolating interim layer such as Octadecanethiol, 4- Nitrobenzenethiol, or MoO2 between the metal substrate and the molecules (Nile Blue). The intensity ratio between the signals taken under resonance and off-resonance conditions was significantly reduced even when these interim layers were only few nanometers thick where EME should not be considerably affected. This was supporting the assumption that CE is the major contribution in the KC SERS experiment.
Due to the domination of the CE, which only involves chemisorbed molecules, the KC SERS arrangement appears to be attractive for applications where thin layers of molecules have to be studied. As an example, we have demonstrated the detection and quantization of a low concentration (100 nM) of Moxifloxacin (Moxi).
The threats posed by climate change require fundamental changes in the nature of the operation of power grids. The increase in fluctuating sources of renewable energy requires flexible and fast-acting control, data processing, and market adjustments. In turn, these lead to complex nonlinear interactions and non-trivial collective fluctuations, which require sophisticated methods of analysis. This dissertation reports on work using a variety of methods from statistical physics to extend the applicability of methods that are already commonly used in control engineering, machine learning, and economic analysis. First, we use the Belief Propagation algorithm (BP), an efficient local algorithm for Bayesian inference, optimization and network analysis, which improves upon Curie-Weiss mean-field theory by taking local correlations into account. We apply the algorithm to statistically analyze conditions under which an accurate estimate of power flows can be obtained from noisy and incomplete measurement sets, and show that it can be used for effective dimensional reduction of power grids. We derive a novel implementation of BP for supply networks, which strongly enhances its convergence and accuracy, explicitly demonstrate its applicability to power grid state estimation and natural gas pipeline network analysis, and discuss further applications to supply networks. Secondly, we map traders' abuse of reserve energy to a minority game and study it using agent-based modeling and the cavity method. The cavity method improves upon Curie-Weiss mean-field theory by including backreactions between traders and market prices, and is formally an approximation on the same level as BP. We show that for this application the cavity method has a natural interpretation in terms of self-consistent linear response. We derive policy recommendations by showing the effectiveness of penalties on large contributors to the abuse of reserve energy, and by demonstrating that external noise is [...]
The family of 2D layered materials has gained enormous attention of materials scientists and researchers from other fields of science. This stems from the fact that 2D monolayers (1Ls) can exhibit remarkably different electronic properties than their bulk counterparts. Moreover, stacking different 1Ls, results in yet different electronic properties than these of the 1Ls. Recently, among others, van der Waals heterostructures (vdW HS) of transition-metal dichalcogenides (TMDC) have been extensively studied due to their type-II band alignment.
This thesis summarizes four different theoretical studies on layered 2D materials. The first study investigates the potential existence of a new family of bulk layered materials with chemical formula XY3 (where X = group 14; Y = group 15). The low cleavage energies indicate the potential exfoliation as mono- and bi- layers (2Ls), where most of the exfoliated layers are thermally and dynamically stable. Interestingly, many 1Ls and 2Ls show strong quantum confinement and turn into indirect semiconductors, unlike bulks which are all metals. Such metal to semiconductor transition was previously known for noble-metal dichalcogenides. Next study shows one of the potential applications of XY3, that is, single-material logical junction for gas sensing applications. A device that consists of metallic multilayers (3L) as electrodes and semiconducting 1L as scattering region. To do so, one of the exemplary materials (SnP3) was picked to construct a single-material device. The results combining density functional theory (DFT) and non-equilibrium Green’s function (NEGF) calculations revealed that SnP3 is an ideal material for gas sensing applications, especially for poisonous NO gas molecules. For NO molecules, this device showed a negative differential resistance (NDR) at small bias voltages.
Moreover, electronic properties of vdW TMDC HS were investigated for the HS having up to six layers. In this part, it was essentially studied [...]
Exfoliation of graphene in 2004 initiated a tremendous interest (both theoretical as well as experimental) in the field of the two-dimensional (2D) materials. Such materials have typically layered structures, so the field of 2D materials is naturally related to the more general field of layered materials. A special (and relatively unexplored) class of such materials are the so-called misfit layered compounds (MLCs), which are made up of layers of 2D crystals whose lattice constant ratio is an irrational number.
Moreover, with the ever growing interest in the chemistry and physics of new materials, there is a high demand for novel and improved theoretical and computational methods, especially for ones which offer accurate, ab-initio theoretical description of large systems (such as the aforementioned MLCs) with low computational costs. One of the methods that seems to meet these demands well is the density-functional based tight-binding.
This thesis is a summary of my work on the above mentioned topics, including:
i) development of new phonon calculation methods in the SCC-DFTB formalism
ii) investigation of layered, intercalated PbNbS2 and misfit (PbS)1.14NbS2 compounds through Raman spectroscopy
iii) investigation of a new family of layered materials, with the formula XY3 (X = group 14, Y = group 15 element)
This thesis covers four topics about organic solar cells to improve the understanding of cell behaviour with models based on physical processes and the influence of degradation.
First, this thesis presents a new model to describe the electrical behavior of solar cells based on physical parameters. This model is based on the assumption of a constant electric field and a linear increasing current in the intrinsic layer (CELIC). As a result, the model describes nicely the currentvoltage (JV) behavior and thereby covers a large range of charge carrier mobilities and illumination intensities. In addition, the crossing point of JV-curves under different illumination intensities can be modeled and correlated to the built-in potential for ohmic contact properties at the interface to the intrinsic layer.
Second, organic solar cell behavior under different illumination levels was tested with the JscVoc method, which allows an investigation of the JV curve without a series resistance. An expression for the series and shunt resistance was developed combining JscVoc and JV analysis. It is shown that the conductivity of the intrinsic layer is associated with recombination processes and is dependent on illumination power. From the findings, a model is presented which splits the recombination and extraction into four illumination dependent regimes.
Third, the influence of the electron and hole blocking layers on the current-voltage characteristics was tested. It was found that the forward current of the solar cells is originating from an exclusive surface recombination current at the semiconductor-ZnO interface.
Forth, the degradation processes in organic solar cells were tested under different external conditions. It was found that the materials and the solar cell do degrade under these conditions by phase separation of the semiconductor mixture, p-doping of the semiconductor, photo-bleaching, and dedoping of the zinc oxide layer.
