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- Design and Optimization of a Wideband Feed Antenna for the Onsala 20-m Telescope(2026) Valsan, AbhijithWideband feed antennas are an essential part of reflector antenna systems, as they affect the radiation characteristics and, in turn, the reflector performance, which is the focus of the present thesis. A wideband quad-ridge horn feed was designed and optimized for the Onsala Cassegrain reflector system. The main objective of this work was to achieve a narrow radiation beam that satisfies the required edge taper while providing acceptable impedance matching and antenna efficiency. The antenna geometry is determined and studied by means of electromagnetic simulation. The ridge profile, horn geometry, and backshort, as well as antenna dimensions and radiation characteristics, were studied in detail. The 3D spline-based approach was used to design the ridge profile, providing flexibility in controlling the antenna geometry. Several geometric configurations and scaling factors were investigated to study their influence on radiation beamwidth and efficiency. The scaled design of 1.8 has shown approximately a 12-degree beam width at -12 dB point at 4 GHz and has retained a narrow beam with the increase of frequency and better antenna efficiency. The efficiency of the antenna has been assessed through simulated reflection coefficient, radiation patterns, spillover efficiency, illumination efficiency and combined aperture efficiency as measuring parameters. Although the target beamwidth could be achieved or closely approached, the overall efficiency remained below the target value of 60%. The results indicate that modifying the geometry and scaling of a wideband quad ridge horn provides significant control over its radiation pattern. Nevertheless, further optimization and validation are required to improve the overall efficiency while maintaining the required beam characteristics.
- Assessing Sustainability Strategic Alignment in Automotive Product Development Decision-Making(2026) Premmert, LeaThe integration of environmental considerations into product development has been discussed in literature with particular attention to approaches related to Life Cycle Assessment (LCA). While these approaches aim to inform more sustainable products and business, a particular gap is the alignment between corporate sustainability strategies and operational decision-making. This study investigates how sustainability goals are operationalized in practice by assessing the strategic alignment between corporate targets and decision-maker priorities, exemplified by a Volvo Cars case study. This study applies the Analytic Network Process (ANP), a Multi-Criteria Decision Analysis (MCDA) method, to two decision cases involving polymeric automotive parts. Six criteria were evaluated: cradle-to-gate carbon footprint, end-of-life circularity, recycled content, biobased content, weight and cost. Data from 79 decision-makers in product development were used to quantify priorities, enabling assessment of strategic alignment. These findings were complemented with interviews with company sustainability experts and participating decision-makers to enable triangulation between strategic ambitions and operational practices, complemented with literature to assess the integration efforts in the case company and synthesize complementary improvement actions. The findings indicated several instances of internal and external misalignment, and misalignment between decision maker preferences and sustainability targets. The integration of environmental considerations into product development decision making was found to be relatively poor, with environmental aspects generally not viewed as an integral part of product development activities. Supplementary interviews and observations revealed that integration efforts from central sustainability functions addressed many of the prescriptions in literature, subsequently addressing much of the identified misalignment. However, a need was identified for top management support and allocation of resources, as well as the creation of dedicated collaboration spaces, to complement central sustainability efforts and to effectively motivate product development staff taking ownership of environmental considerations This study is a relevant example of current challenges present in environmental work and green product development, with a particular focus in the automotive industry. It also demonstrates how a quantitative method like ANP can be combined with qualitative analysis and an extended scope of respondents to assess misalignment between sustainability strategy and decision-making practices in complex industrial contexts.
- Edge-Optimized Deep Learning for Real-Time State of Health Estimation of Lithium-Ion Batteries in Embedded Systems(2026) Hanumaraddi, Krishna; Fu, XuqiAccurate State of Health (SoH) estimation is critical for lithium-ion battery management. While deep learning models like Long Short-Term Memory (LSTM) networks offer superior predictive capabilities, their computational complexity and memory footprints prohibit direct deployment on resource-constrained Battery Management System (BMS) microcontrollers. This thesis addresses this bottleneck by proposing an edge-optimized deep learning framework for real-time SoH estimation. Utilizing features extracted from early-cycle operational data (the first 10 cycles), we develop a Physics-Informed Long Short-Term Memory (PINN-LSTM) architecture as the fullprecision teacher model. To achieve embedded compatibility, we introduce a model compression pipeline integrating Physics-Informed Neural Network Knowledge Distillation (PINN-KD), structural pruning, and W8A32 dynamic quantization, where the knowledge of the PINN-LSTM teacher is transferred to a lightweight LSTM student model. The optimization workflow compiles the models from PyTorch into bare-metal C applications using the Apache TVM stack and Relax Virtual Machine, enabling static memory allocation and Flash-aligned weight storage. Software-inthe- Loop (SIL) on Infineon TC4D7 and Processor-in-the-Loop (PIL) evaluations on NXP MCXN947 microcontrollers validate the system’s real-time performance and concurrent asynchronous data handling. Results demonstrate a massive memory reduction, with Flash storage shrinking from 127.13 KB (full-precision PINN-LSTM teacher) to merely 1.25 KB (quantized LSTM student). Crucially, the W8A32 quantized student model maintains exceptional mathematical fidelity, exhibiting a Mean Absolute Error (MAE) of 3.32×10−8 against the corresponding full-precision LSTM student model. Finally, the study identifies gradient dominance as a fundamental challenge in developing chemistry-agnostic models across mixed LFP, NMC, and NCA datasets, highlighting avenues for future domain-adaptation research.
- Multi-functional Microneedle Patches for Chronic Wound Infections(2026) Eriksson, Caroline; Ramér, ElinBacterial infections can persist as biofilms in wounds, exacerbating infection and potentially causing it to become chronic. Biofilms are difficult to treat because of their robust protective structure that limits antibiotic delivery, while their microenvironment can promotes the spread of antibiotic resistance. Because antibiotics often fail to eradicate established biofilms, removal typically requires surgical debridement, which is costly, time-consuming, and invasive. New treatment strategies are therefore needed to effectively disrupt established biofilms, kill planktonic bacteria, and enable minimally invasive drug delivery. Microneedle patches (MNs) are promising drug delivery systems due to their biocompatibility, tunable mechanical properties, and swelling capacity. Loaded with therapeutics, MNs combine needle penetration with swelling to release of therapeutics deeper into infected tissue. This study assesses the therapeutic effect of two MN designs, NaBIL@MN and MV-ZnO@DMN, on methicillin-resistant Staphylococcus aureus (MRSA) biofilms. Both MNs were successfully fabricated with therapeutic incorporation, sufficient thermal stability and mechanical strength for skin penetration. The MNs showed two distinct hydration behaviours. NaBIL@MN demonstrated swelling behaviour with potential for controlled drug release, while MV-ZnO@DMN rapidly dissolved, likely resulting in burst release. Biological testing demonstrated antibiofilm activity of membrane vesicles (MVs) against MRSA both free form and loaded into the DMN system. ZnO nanoparticles (ZnO NPs) exhibited a minimum inhibitory concentration (MIC) of 100 μg/ml against MRSA, but were cytotoxic at concentrations above 25 μg/ml. Consequently, although MV-ZnO@DMN showed antibiofilm activity, its antimicrobial effect was insufficient to kill bacteria remaining in the biofilm. NaBIL@MN prevented biofilm formation and showed potential dispersive activity against mature biofilms. However, despite significant antimicrobial activity against planktonic MRSA, it did not significantly reduce the viability or growth of bacteria remaining in the biofilm after dispersion. Furthermore, although NaBIL@MN showed clinically acceptable cell viability above 70 %, compromised cell morphology and cell number, together with hemolytic activity exceeding clinical standards, suggest limited biocompatibility. Nevertheless, these findings demonstrate the potential of NaBIL@MN and MV-ZnO@DMN as drug delivery systems against MRSA biofilms while highlighting the challenge of balancing antimicrobial efficacy and cytocompatibility.
- Direct Detection of Light Dark Matter in the Scotogenic Model(2026) Ellermeier, Jan OleThe scotogenic model, also known as the radiative seesaw model, provides an elegant theoretical framework that simultaneously accounts for the generation of active neutrino masses and the existence of dark matter. Current realisations of the model typically focus on weakly interacting massive particle (WIMP) dark matter candidates with masses above the GeV scale. However, despite decades of direct detection searches, no conclusive evidence for WIMP dark matter has yet been found. One possible explanation for this null result is that dark matter may lie below the GeV scale, where conventional nuclear-recoil experiments lose sensitivity due to kinematic thresholds. This possibility motivates the study of sub-GeV realisations of the scotogenic model. This thesis carries out that study for Majorana dark matter in the minimal scotogenic model. Assuming a 𝜏-philic flavour structure, the leading-order electromagnetic interaction is a loop-induced anapole moment. Non-relativistic effective field theory then yields the inelastic scattering cross-section against bound atomic electrons in liquid xenon. Confronting these rates with XENON1T data places upper limits on the anapole coupling, and identifies a steep loss of sensitivity below a dark matter mass 𝑀1 ≈ 30 MeV, driven by the quantisation of the ionisation signal. The pipeline reproduces the published XENON1T anapole constraint to within 3%. Enforcing the LEP bound on the scalar mediator mass (𝑚𝜂± ≳ 90 GeV), the thermal relic density requires non-perturbative couplings (𝑦 > √4𝜋) below 𝑀1 ≈ 480 MeV, while XENON1T only excludes unphysical values (𝑦 ≳ 265). Thermal freeze-out therefore survives only for 𝑀1 ≳ 480 MeV, with the mediator confined to a 37 GeV window above the LEP bound and a coupling close to the perturbative ceiling. Even there the thermal target lies two orders of magnitude below the XENON1T reach in coupling. Below that window the model requires non-thermal freeze-in production, suppressing the scattering rate by roughly 45 orders of magnitude. In neither case is direct detection the discovery channel, and verification shifts to collider searches for the long-lived charged mediator.