This report is a summary of the physical background and experimental work conducted during the MA3 specialization semester in the autumn semester 2025/2026, focusing on Resonant Inelastic X-ray Scattering (RIXS). Two RIXS experiments on different quantum materials are performed and analyzed. The first study investigates the excitonic insulator candidate GdGaI and its temperature-dependent electronic excitations, aiming to probe potential excitonic signatures. Atomic multiplet calculations were performed to understand the experimental RIXS results. The second study focuses on Sr-doped La3Ni2O7 thin films, where RIXS is used to examine the doping dependence of magnetic and orbital excitations and their connection to superconductivity.

The global construction industry contributes 37% of energy-related carbon emissions and it is mandated to achieve a 50% reduction in carbon emissions by 2030 as a crucial step towards achieving net-zero targets by the mid-century. As we strive for low-carbon buildings that align with these targets, it is imperative to ensure buildings are comfortable for their inhabitants. Daylight, valued for providing illumination and enhancing well-being, is a key component that also influences the building's carbon emissions. The existing daylight standards encourage larger glazed areas, which often results in larger solar gains in the summer and heat losses in the winter, and therefore in larger shading systems, thicker frames and multiple panes of glass. These directly influence the embodied impacts of the building, as a result of the façade's material and components choices. Yet the interactions between daylight and embodied impacts have so far largely remained overlooked in design decision-making. More specifically, there is currently no guidance on what reasonable carbon budget should be associated with daylight design choices, even though these choices may influence a building's ultimate carbon footprint at least to some extent. This study aims to uncover the relationships that (may) exist between daylight strategies and embodied impacts and to propose an explorative methodology able to support daylight-driven decisions accounting for carbon budget constraints. The method is applied to a specific case study, which further highlighted the increasing urgency of accounting for these interactions from the year 2040 onwards.

Office employees are influenced by various environmental and contextual factors that prompt interaction with building interfaces, such as adjusting windows or blinds. These behaviours can impact predictions of buildings' performance. While occupant behaviour models often rely on physical variables, they tend to overlook users' actual motivations and how these interact. This study introduces a novel mobile application, OBdrive, that uniquely captures occupants' motivations in real-time, offering direct insights into why users operate windows, blinds, and lights. OBdrive forms a central element of the eCOMBINE framework ("Interaction between energy use, COMfort, Behaviour and the INdoor Environment in office buildings"), applied across five monitoring campaigns in two open-plan offices in Switzerland. The analyses highlight the diverse range of motivations underlying occupants' interaction with windows and blinds. In addition to single environmental drivers (e.g., 45 % of window-open actions in response to warm discomfort), multi-domain discomforts often act in combination to prompt adaptive behaviours (e.g., 32 % of the recorded opening windows actions were linked to the cooccurrence of warm discomfort and poor air quality). Occupants' behaviour (e.g., window closing actions) can be linked to time-related and contextual factors, such as departing office and requirements from co-workers. The findings demonstrated that both explicit and "hidden" motivations (e.g., co-worker asked, save energy, mask noise) drive human-building interactions (HBIs), and that these motivations are rarely captured in traditional field studies. Therefore, the eCOMBINE framework, along with the OBdrive application, offers a means to unravel the combinations of motivations driving occupant behaviours in buildings.

Komorebi, the dappled sunlight filtering through trees, offers restorative benefits in outdoor and indoor environments. While studies have examined its presence, movement, and changes in illuminance, a comprehensive understanding of its dynamic properties remains largely unexplored. This study develops a framework to quantify the spatial and temporal characteristics of Komorebi patterns. The methodology involves collecting Komorebi scenes, extracting their temporal and spatial features, and creating a multidimensional representation to capture these features effectively. The spatial feature analysis focuses on light pattern dispersion, intensity correlations, and spectral analysis of two-dimensional patterns; the temporal analysis, on the other hand, examines movement, directional changes, and brightness fluctuations. This study introduces a novel approach for categorizing and representing different typologies of Komorebi, and establishes a basis for examining people's responses to Komorebi patterns.

In this study, we examined the influence of daylight transmitted through colored glazing on discomfort glare by exposing 56 participants to four daylight conditions with the sun disc visible in their field of view. The conditions varied only in the glazing color (red, blue, green, and neutral) toward the sun while having similar transmittance and glare metric values. Results showed a strong influence of color on glare perception, with more participants reporting glare under red and blue conditions compared to green and neutral ones. These findings indicate that V(λ) is not an effective method for spectral weighting in colored lighting scenarios and that the Helmholz-Kohlrausch (H-K) effect may apply to glare similar to brightness perception. To incorporate this effect in glare model, we implemented the CIE200:2011 supplementary photometry system which integrates the H-K effect and results in better glare prediction in colored daylit scenes.

Dwarf galaxies are the most common type of galaxy in the Universe and have emerged as powerful testbeds for our standard cosmological model LambdaCDM on small scales, where several tensions persist. This thesis focuses specifically on the phase-space distribution of dwarf satellites around massive hosts. Several nearby hosts, including the Milky Way, appear to have flattened, kinematically correlated satellite configurations that are uncommon among LambdaCDM analogs---the planes-of-satellites challenge. Robust tests require large, contamination-controlled satellite samples across diverse environments, which are challenging to obtain beyond the Local Group because dwarfs are intrinsically faint and generally have low surface brightness. This thesis contributes to the extension of phase-space studies beyond the Local Group by (i) evaluating and refining methods to quantify phase-space distributions, in particular lopsided satellite distributions and planes-of-satellites, and conducting statistical tests on such distributions in existing survey data (e.g., MATLAS, ELVES); (ii) expanding line-of-sight velocity coverage via VLT/MUSE spectroscopy of MATLAS candidates and establishing host membership; and (iii) developing an automated pipeline, combining classical methods with deep learning, to build a survey-scale catalog of dwarf galaxy candidates in the wide-field UNIONS survey. Across 68 host systems in MATLAS/ELVES, ~21% show significant lopsidedness with the signal strongest at larger projected radii, consistent with recent accretions and in line with LambdaCDM expectations. Follow-up on reported candidate planes generally revealed no significant tension with LambdaCDM when revisited with new data. An exception to this trend is the NGC 4490 group, where such a highly correlated structure was identified as uncommon in simulated analogs. In the MUSE program, we confirmed 75% of the MATLAS dwarfs in the sample as satellites; non-members tend to be late-types, supporting morphology as a membership prior. Our pipeline yielded dwarf probability scores for 1.5 million selected objects, producing the Galaxies OBserved as Low-luminosity Identified Nebulae (GOBLIN) catalog. GOBLIN contains ~43,000 high probability (>=0.8) dwarf candidates, which represents a significant increase in the number of high-confidence candidates in the local Universe. Taken together, the majority of our investigations into phase-space distributions of dwarfs revealed consistency with LambdaCDM given current data. There are, however, noteworthy exceptions, and several systems are still far from complete in terms of distance and velocity estimates. Such measurements are necessary to draw definitive conclusions. Our publicly available GOBLIN catalog contains a large sample of high-probability dwarf candidates, laying the foundation for targeted follow-up campaigns and future phase-space studies.

Millions of people around the world suffer from neurodegenerative diseases. While specific treatments may be able to relieve some of the symptoms of neurodegenerative diseases, in most cases, these complex neurological disorders do not have a cure as we do not completely understand the cause of the disease. The current theory for the mechanism of neurodegenerative diseases is that the causative protein misfolds into a beta-sheet conformation triggering the formation of amyloid fibrils that aggregate into distinctive cellular inclusions. One such protein is alpha-synuclein (aSyn) which accumulates into fibrils in Parkinson's disease (PD), dementia with Lewy bodies (DLB), and multiple system atrophy (MSA). When aSyn amyloid fibrils clump together in diseases such as PD and DLB, they form Lewy bodies. As amyloid fibrils are thought to be the causative agent of the disease, many therapeutic strategies are being developed to inhibit the formation of the fibrils. To facilitate structure-based drug design, several methods have emerged in recent years to generate disease fibrils in vitro and obtain the atomic resolution 3D structure using cryo-electron microscopy. Of the many structures which are emerging from these studies, one major question is if these in vitro-generated structures are the same as what is seen in human disease. In this research, I will use multiple electron microscopy approaches to understand the physiological structure of aSyn fibrils in DLB, which is the second most common form of dementia after Alzheimer's disease. My first aim is to determine the in vitro structure of aSyn fibrils extracted from DLB patients. Cryo-EM is a tool that allows us to get the high-resolution structure of the fibrils in native conditions by plunge freezing in liquid ethane. Several software packages have been developed for electron microscopy structure determination, including RELION (REgularised LIkelihood Optimization); My second aim is to use room-temperature correlative light and electron microscopy (CLEM) method on resin-embedded brain sections to obtain the global morphology of aSyn inclusions in DLB brain donors. The inclusions will be first localized in the brain slices by fluorescence microscopy, and the structure will be analyzed by electron microscopy and electron tomography. I will investigate the inclusions in different brain regions and multiple patients. This analysis will inform us about different inclusion types present in DLB brains and define the targets for high-resolution cryo-CLEM; My final aim is to obtain the high-resolution structure directly within post-mortem human brain samples by cryo-CLEM. This will provide a direct representation of the pathological fibril structure, which can be used for drug discovery and mouse models. Cryo-CLEM and CLEM will be used to study the fibrillar structures in different parts of the post-mortem human brain with DLB. By correlating the information from post-mortem human brains with in vitro fibril structures, I can identify the specific fibril strain which makes up the pathology seen in DLB and PD. The results of this study may lead to the discovery of new therapeutic approaches for synucleinopathies and, in particular, for the prevention or slowing of neurodegeneration associated with Lewy Body diseases.

The kinetic inertness and low solubility of Au3(pyrazolate)3 complexes have made it difficult to integrate them into supramolecular assemblies. In this thesis, an investigation into the dynamic combinatorial chemistry of these complexes is presented, followed by strategies for their incorporation into molecular cages and a study of the host - guest chemistry of the resulting assemblies. The first research chapter, Chapter 2, describes the constitutional dynamic chemistry of Au3(pyrazolate)3 complexes. Ligand exchange reactions between"free" pyrazole ligands and Au3(pyrazolate)3 complexes were performed, and a pronounced autocatalytic behavior was observed. This led to the understanding that pyrazole ligands can act as catalysts for ligand scrambling between two Au3(pyrazolate)3 complexes. In addition, four crystal structures of heteroleptic Au3(pyrazolate)2(pyrazolate') are presented. Building on this foundation, Chapter 3 describes the synthesis of a dodecanuclear Au(I) cage. The cage consists of four Au3(pyrazolate)3 units, connected through an organic linker. The cage was first synthesized by a ligand exchange reaction, using an Au3(triazolate)3 complex as a gold source. Surprisingly, the same cage was also obtained in a direct synthesis from a reaction with AuCl(SMe2). The results highlight the importance of ligand design for the successful formation of Au3(pyrazolate)3-based cages. In Chapters 4 and 5, we demonstrate how the kinetic inertness of Au cyclic trinuclear complexes (CTCs) can be utilized in order to use them as pre-formed building blocks for cage synthesis. In Chapter 4, a stepwise approach, in which the use of metalloligands enabled the construction of a Fe24Au24Pd8 cage, is presented. With a molecular weight of 21 kDa and a diameter of approximately 4.1 nm, it is among the largest [Pd6L8]12+ cages reported. In addition, we demonstrate the use of a heteroleptic Au3(pyrazolate)2(pyrazolate') complex for the construction of a smaller Fe8Au12Pd2 cage. In Chapter 5, the preparation of three Au3(pyrazolate)3-based cages by combining coordination chemistry and dynamic covalent chemistry is described. First, two Au3(pyrazolate)3 complexes bearing peripheral aldehyde groups were synthesized. These complexes were used as building blocks for an imine condensation reaction, yielding one tetrahedral cage, containing four CTC units, and two prismatic cages, containing two CTC units each. The crystal structures of all three assemblies are reported. In addition, the host-guest chemistry with pi-acidic guests was studied: the tetrahedral cage was found to bind fullerenes with high affinity, while the prismatic cages encapsulate halogenated aromatic compounds. In Chapter 6, the combination of coordination chemistry and dynamic covalent chemistry for the synthesis of a new family of zirconium-based cages is presented. Pre-formed zirconium clusters were employed as rigid, preorganized building blocks, leading to the synthesis of four new cages: a compact [1+1] species, a [2+3] architecture, and two large tetrahedral [4+4] cages.

For decades, cancer biology research has primarily focused on intrinsic tumor mechanisms driven by genetic lesions. It is now clear that tumor cell behavior is shaped by additional layers of regulation, including epigenetic modifications and metabolic reprogramming, which confer high plasticity and render cancer cells highly responsive to cues from their surrounding microenvironment. Continuous cross-talk between tumor cells and the diverse components of the tumor microenvironment dictates tumorigenesis and is often skewed toward pro-tumoral signals, thereby fueling cancer progression. In B-cell lymphomas, a heterogeneous group of malignancies arising from mature B cells, immune-tumor interactions are particularly important, especially in early disease and indolent subtypes. The increasingly precise understanding of these interactions has recently driven the development of immune-based therapies, which have achieved transformative results in both lymphomas and solid tumors. Nevertheless, tumors continuously adapt and evade immune control, and relapsed or refractory cancers remain largely incurable despite recent advances. Overcoming these limitations requires novel therapeutic strategies and preclinical models that reproduce the complexity of human disease.

In this thesis, I describe a strategy to enhance anti-cancer immunity by targeting long-chain fatty acid (LCFA) elongation. By combining high-throughput drug screening with proteomics, lipidomics, and genetic engineering, we identified Phago Booster 1 (PB1), a small-molecule inhibitor of HSD17B12, a key enzyme in LCFA elongation. Targeting HSD17B12 selectively altered membrane organization in cancer cells, leading to the redistribution of surface receptors, including immune checkpoints and lipid transporters. In contrast, HSD17B12 inhibition enhanced the cytotoxic capacity of immune cells by increasing their glycolytic activity, thereby promoting activation. This divergent effect proved therapeutically relevant in vivo, leading to slower tumor growth and improved survival without notable toxicity. In parallel, I contributed to the development of a patient-derived lymphoma tissue explant platform designed to preserve native tumor architecture, stromal components, and immune cell diversity. We demonstrated that this system, termed lymphomoids, can support personalized medicine approaches by enabling the ex vivo assessment of patient-specific therapeutic responses. In a pilot cohort of 8 patients, drug sensitivity in lymphomoids successfully matched clinical outcomes in 89% of cases, highlighting its potential as a predictive tool for guiding treatment selection.

Together, these approaches illustrate how combining innovative therapeutic discovery with physiologically relevant disease models can uncover actionable strategies to overcome immune resistance and advance personalized cancer treatment.

Three-dimensional (3D) imaging has become an increasingly important research field, with applications spanning the automotive industry, consumer electronics, bioimaging, virtual and augmented reality, and space instrumentation. Real-time, high-frame-rate imaging in such demanding environments requires the acquisition of large data volumes at high readout speeds, while simultaneously maintaining low noise levels to ensure high-quality depth reconstruction.

Direct time-of-flight (dToF) imaging has emerged as a compelling candidate for these applications. By combining light detection and ranging (LiDAR) techniques with low-noise, high-sensitivity photodetectorsâ such as single-photon avalanche diodes (SPADs)â and accurate timing circuits, including time-to-digital converters (TDCs) and time-gating architectures supported by phase-locked loops (PLLs), sub-nanosecond timing precision can be achieved. This level of precision enables millimeter-scale depth resolution, even under challenging operating conditions.

This thesis focuses on improving the frame rate of SPAD-based dToF integrated circuits (ICs). Although LiDAR is used as the primary application example, the concepts and methods presented here are broadly applicable to other imaging domains, provided that the pixel front-end is adapted accordingly. The work begins with the characterization of a 45~nm/22~nm 3D-stacked SPAD imager featuring on-chip data processing. Both architectural and device-level measurements were performed, and the insights gained from this characterization informed the subsequent IC developments.

Leveraging this experience, three additional CMOS SPAD imagers were designed. Each implementation explores different architectural strategies aimed at improving frame rate and signal-to-noise ratio (SNR). One line of work focuses on scalable and uniform coincidence detection to ensure consistent performance across the array. Another introduces event-driven readout, allowing the system to transmit data only when changes occur in the scene, thereby reducing bandwidth and improving temporal efficiency. Nearly all functional blocks were designed to be programmable, enabling proof-of-concept evaluation across a wide range of operating conditions, including long-range and low-light scenarios.

In summary, this thesis introduces several new techniques for on-chip data processing in SPAD imagers, including a novel coincidence architecture and a dual-threshold digital event-based processing scheme. It is anticipated that the contributions of this work will support future advances in high-speed 3D imaging and enable further scientific and technological developments in the field.\