Physics

Title of thesis:&nbsp;Explainable AI for Decision Making
Abstract:&nbsp;This thesis explores the use of a Retrieval Augmented Generation (RAG) AI system, built on Large Language Models (LLMs), to support root cause analysis of quality issues in industrial and marine power systems. Conducted in collaboration with Volvo Penta, the study evaluates whether pre-trained LLMs and a tailored database can operate effectively in a specialized domain.&nbsp;
Examiner: Mats Granath Supervisor: Bettina Linder Opponents: Kevin To &amp; Joel Gråsjö&nbsp;
Location of presentation: <a rel="noopener" href="https://maps.chalmers.se/#7241f650-27c9-11ef-a21b-017390dd2bcd" target="_blank" title="Chalmers maps" data-anchor="#7241f650-27c9-11ef-a21b-017390dd2bcd">von Bahr, Soliden 3</a><a rel="noopener" href="https://maps.chalmers.se/#24d8b7be-1f59-4388-be28-a07861b429b2" target="_blank" title="Chalmers Maps" data-anchor="#24d8b7be-1f59-4388-be28-a07861b429b2"></a><a rel="noopener" href="https://maps.chalmers.se/#36a610c1-e9b3-48bd-b01c-9501f9af79fe" target="_blank" title="Chalmers map" data-anchor="#36a610c1-e9b3-48bd-b01c-9501f9af79fe"></a>
Online: <a rel="noopener" href="https://chalmers.zoom.us/j/68569050177" target="_blank" title="Zoom">Zoom</a>

Title of thesis:&nbsp;<span style="font-size: 11.0pt; font-family: 'Aptos',sans-serif; mso-fareast-font-family: Calibri; mso-fareast-theme-font: minor-latin; mso-bidi-font-family: Aptos; color: black; mso-ligatures: standardcontextual; mso-ansi-language: EN-GB; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;" lang="EN-GB">Diagnosing Brachycephalic Obstructive Airway Syndrome in Dogs Using Computer Vision and Machine Learning
Abstract:&nbsp;
Brachycephalic Obstructive Airway Syndrome (BOAS) is a breathing disorder that is common among dogs of certain breeds, impairing their quality of life. Diagnosing BOAS requires licensed veterinarians to undergo specialized training, which limits accessibility. There is demand for a more accessible solution, which artificial intelligence could provide. This thesis evaluates two different approaches of machine learning to explore the possibility of classifying BOAS based on audio recorded from Android mobile phones, using Python. The first approach extracts signal features from the audio, which are used to train a simple machine learning model. The second approach relies on computer vision, using spectrograms; visual representations of the audio signals, to train a Convolutional Neural Network (CNN). Due to limited data, I employed augmentation techniques to artificially expand the dataset for training the models. My findings suggest that the spectrogram-based model is better suited for the problem, with a perfect prediction accuracy when the dogs were recorded after a short exercise test, suggesting strong performance under that condition. For dogs at rest, this model achieved an 81.7% accuracy, indicating somewhat promising results even under less favourable conditions. However, due to the limited dataset, the predictive performance was evaluated on few samples, and therefore additional data is needed for a more robust conclusion. Furthermore, one particular augmentation technique designed to account for differences in the recording devices' frequency response enhanced the model's general performance and could be further refined to improve accuracy, especially for dogs at rest.
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Examiner: Magnus Karlsteen Supervisor: Magnus Karlsteen Opponent: Jennie Berndtson
Location of presentation: <a rel="noopener" href="https://maps.chalmers.se/#eece58ce-9a1e-4ab1-af3d-d4fc2cb1126c" target="_blank" title="Chalmers map" data-anchor="#eece58ce-9a1e-4ab1-af3d-d4fc2cb1126c">Nexus, Fysik Origo</a>

Title of thesis: Acoustic Signal Analysis and Feature-Based Classification of BOAS:&nbsp;For the Health and Welfare of Brachycephalic Dogs
Abstract:&nbsp;
Brachycephalic Obstructive Airway Syndrome (BOAS) is a chronic condition that significantly impairs breathing and reduces the quality of life in popular brachycephalic dog breeds such as Bulldogs, French Bulldogs, and Pugs. As these breeds become more popular, the number of affected dogs increases, highlighting the need for accessible and reliable methods to assess the severity of BOAS.
Currently, BOAS is diagnosed through a functional grading test performed by certified veterinarians. However, the limited availability of accredited professionals restricts access to this test. As of early 2025, Swedish law requires all brachycephalic dogs to pass this test to be eligible for breeding, further increasing the demand for accessible testing solutions.
This thesis explores using acoustic signal analysis and machine learning to classify dogs as BOAS-positive or BOAS-negative based on their breathing sounds. Audio recordings from several dogs were analyzed, with features extracted using the openSMILE toolbox. The Mann-Whitney U-test was then applied to reduce the feature set to those most correlated with BOAS classification.
Two modeling approaches were tested, one using separate models for pre- and post-exercise data and a hybrid model combining both. The hybrid model performed best, with statistical analysis showing post-exercise data to be more informative. The final model correctly classified all five dogs in the new dataset, achieving an AUC of 1.0 and an average prediction confidence of 86.8%. These results show promising potential for an acoustic, feature-based BOAS classification model, though additional data is needed to improve its generalization.
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Examiner: Magnus Karlsteen Supervisor: Magnus Karlsteen Opponent: Tim Pagrell
Location of presentation: <a rel="noopener" href="https://maps.chalmers.se/#eece58ce-9a1e-4ab1-af3d-d4fc2cb1126c" target="_blank" title="Chalmers map" data-anchor="#eece58ce-9a1e-4ab1-af3d-d4fc2cb1126c">Nexus, Fysik Origo</a>

Title of thesis:&nbsp;Multivariate anomaly detection with LSTM layered Variational Autoencoder
Abstract:The aim of this thesis was to develop and evaluate the effectiveness of a recurrent neural network layered autoencoder model for detecting anomalies in multivariate time-series data, with a focus on improving the accuracy and reliability of diagnostic data for Volvo Penta’s boats. The primary goal was to leverage the relationships and correlations between signals to identify deviations that traditional models may fail to detect. The model’s performance was assessed in terms of its ability to learn the structure of normal data, detect synthetic anomalies, and provide meaningful insights without relying on labeled datasets.
Examiner: Mats Granath Supervisor: Mats Granath Opponents: Atefeh Mirzbeigi, Amir Ali Barani, Sean Lidin
Location of presentation: <a rel="noopener" href="https://maps.chalmers.se/#7241f650-27c9-11ef-a21b-017390dd2bcd" target="_blank" title="Chalmers maps" data-anchor="#7241f650-27c9-11ef-a21b-017390dd2bcd">von Bahr, Soliden 3</a><a rel="noopener" href="https://maps.chalmers.se/#24d8b7be-1f59-4388-be28-a07861b429b2" target="_blank" title="Chalmers Maps" data-anchor="#24d8b7be-1f59-4388-be28-a07861b429b2"></a><a rel="noopener" href="https://maps.chalmers.se/#36a610c1-e9b3-48bd-b01c-9501f9af79fe" target="_blank" title="Chalmers map" data-anchor="#36a610c1-e9b3-48bd-b01c-9501f9af79fe"></a>
Online: <a rel="noopener" href="https://chalmers.zoom.us/j/66477666274" target="_blank" title="Zoom">Zoom</a>

Title of thesis: More Reliable Binding Affinity Prediction of Protein Ligands Combining Molecular Dynamics Simulations and Machine Learning Models
Abstract: Efficient and accurate prediction of protein-ligand binding affinities is essential for advancing drug discovery. This thesis presents a novel approach that combines molecular docking results with features derived from short molecular dynamics(MD) simulations to enhance the prediction accuracy of binding affinities. The thesis aims to bridge the efficiency of traditional docking methods with the more accurate Free Energy perturbation (FEP) techniques. MD simulations were conducted on a dataset of around 5,000 protein-ligand complexes and extracted features related to binding enthalpy and dynamic behavior related to the more complex binding entropy. These features, alongside molecular docking scores, were used to train machine learning models. The CatBoost regressor was identified as the most effective model, achieving better predictive accuracy than Molecular Docking alone. This method facilitates more reliable binding affinity predictions by successfully integrating docking insights with dynamic protein-ligand behavior, thereby accelerating the early stages of drug discovery.
Examiner: Paul Erhart Supervisors: Marco Klähn Opponent: Richard Nunstedt and Erik Linghammar
Location of presentation: <a rel="noopener" href="https://maps.chalmers.se/#24d8b7be-1f59-4388-be28-a07861b429b2" target="_blank" title="Chalmers map" data-anchor="#24d8b7be-1f59-4388-be28-a07861b429b2">PJ-salen</a>

Title of thesis:&nbsp;On the Feasibility of Neutron Noise Diagnostics in Fast Gen-IV Reactors – Comparisons of One-Dimensional Neutron Noise Characteristics in Fast and Thermal Systems using Linear Multi-Group Diffusion Theory
Abstract: This master's thesis studies neutron noise, i.e. the temporal fluctuations from the mean neutron flux, in nuclear reactors. Neutron noise can be used to identify and localise faults and anomalies in such systems through a technique called neutron noise diagnostics, potentially providing early warning and leading to increased safety and operational availability. Due to the limited amount of neutron flux instrumentation available in a typical power reactor, the spatial shape of the noise is the key quantity to characterise the type of noise present. This study differentiates itself from prior research on neutron noise diagnostics, which mostly focused on Light-Water Reactors (LWR), whereas this work investigates the properties of the neutron noise in both LWRs and in Liquid Metal-cooled Fast Reactors (LMFR). More specifically, we compare the axial shape of the neutron noise of: Pressurised Water Reactors (PWR), Boiling Water Reactors (BWR), Sodium-cooled Fast Reactor (SFR) and Lead-Cooled Fast Reactors (LFR). The former two are LWRs, and the latter two are LMFRs. Each system's deviation from point kinetics is analysed, which is essential to evaluate the capability of noise diagnostics.
To this end, a 1D numerical neutron transport solver was developed using linear multi-group diffusion theory with a variable number of delayed neutron families. The solver uses group constants generated by the Monte Carlo code Serpent-2 for each modelled system. The static neutron flux is described by an eigenvalue problem, which is solved by the power iteration method, accelerated using Wieland's technique. The induced noise arises from an absorber of variable strength-type perturbation in the macroscopic absorption cross-section, and the resulting source-type problem is solved by matrix inversion.&nbsp;
Our computations show that the induced neutron noise of the LWRs deviates more from point-kinetics, and their axial shape is thus more informative than that of the LMFRs. Also, perturbations closer to the reactor's periphery induce a neutron noise that is more informative. The point-kinetic behaviour of the LFR is strongly dictated by the active height of the core, more so than by the fast spectrum. We also show that reactors fuelled by plutonium are more point-kinetic than those fuelled by uranium.
For the results to become more conclusive, more work is needed regarding the types of reactors studied, with more analysis aimed towards what parameters affect the point-kinetic nature of the noise. Studies can also be made in higher spatial dimensions that more accurately take into account the complex geometries of nuclear reactors, and incorporating burn-up calculations when generating the group constants.
Examiner: Christophe Demaziere Supervisors: Christophe Demaziere Opponent: Pablo Arriagada Torres
Location of presentation: <a rel="noopener" href="https://maps.chalmers.se/#24d8b7be-1f59-4388-be28-a07861b429b2" target="_blank" title="Chalmers map" data-anchor="#24d8b7be-1f59-4388-be28-a07861b429b2">PJ-salen</a>

Title of thesis:&nbsp;Characterization of solid electrolytes and sodium metal anodes
Abstract:&nbsp;Solid-state sodium batteries are possible candidates for next-generation electrochemical energy storage, with improved sustainability and safety over current lithium-ion technologies. In addition, solid electrolytes could potentially enable the use of sodium metal anodes for increased energy density. However, these electrodes currently have short lifetime due to electro-chemo-mechanically coupled degradation mechanisms, which need to be well understood in order to mitigate the problems and extend the lifetime of solid-state sodium batteries. This thesis investigates a sulfide solid electrolyte, with a particular interest in processes at the interface with sodium metal. The study involves electrochemical characterization techniques and imaging with X-ray tomographic microscopy, in order to gain insights into the processes that limit cell lifetime and efficiency. Results show rapid polarization of the cells, likely caused by chemical degradation between sodium metal and the electrolyte. The reaction products seem to form an interphase layer that fails to passivate the electrode, leading to capacity loss due to the continuous consumption of sodium metal. Protective interlayers could be a promising path of future research in order to improve the interface stability and extend the lifetime of sodium metal electrodes.
Examiner: Aleksandar Matic Supervisors: Elin Dufvenius Esping Opponent: Simon Dovrén
Location of presentation: <a rel="noopener" href="https://maps.chalmers.se/#24d8b7be-1f59-4388-be28-a07861b429b2" target="_blank" title="Chalmers map" data-anchor="#24d8b7be-1f59-4388-be28-a07861b429b2">PJ-salen</a>

Title of thesis: <span style="font-size: 12.0pt; font-family: 'Aptos',sans-serif; mso-fareast-font-family: Calibri; mso-fareast-theme-font: minor-latin; mso-bidi-font-family: Aptos; color: black; mso-ansi-language: SV; mso-fareast-language: SV; mso-bidi-language: AR-SA;">Water-induced phase separation in amorphous solid dispersions studied with SAXS
Abstract:&nbsp;Amorphous solid dispersions (ASDs) are pharmaceutical formulation in which a drug is molecularly dispersed within a carrier matrix. ASDs are designed to address the challenges of drugs with low solubility in their crystalline state. The carrier matrix, typically a polymer, helps stabilizing the drug in its amorphous phase, which allows ASDs to enhance solubility and dissolution rates. This thesis examines ASDs composed of the drug indomethacin and the polymer PVPVA as carrier, with the objective to correlate water-induced phase separation to drug release behaviour. Samples of varying drug concentrations, both in their dry state and after exposure to a neutral buffer, were analysed using small-angle X-ray scattering (SAXS), to understand the phase separation processes on the nanoscale. &nbsp;The mobility of the samples was analysed with differential scanning calorimetry (DSC) and the drug release was measured through dissolution tests. Nanoscale phase separation occurred upon exposure to a neutral buffer, for drug loadings &gt;10%, after absorbing &gt;40% buffer. Higher drug loadings and buffer concentration led to a higher degree of phase separation with distinct interphases. This impacted the dissolution properties, as samples with 5% and 10% drug loading had faster drug release, in comparison to the 20% and 30% samples. &nbsp;These results offer insight into the phase behaviour of ASDs upon dissolution, though additional investigation of ASDs in acidic conditions would enhance the understanding of in vivo phase separation processes.
Examiner: Aleksandar Matic Supervisors: Martina Olsson Opponent: Andreas Erlandsson
Location of presentation: <a rel="noopener" href="https://maps.chalmers.se/#24d8b7be-1f59-4388-be28-a07861b429b2" target="_blank" title="Chalmers map" data-anchor="#24d8b7be-1f59-4388-be28-a07861b429b2">PJ-salen</a>

Title of thesis:&nbsp;<span style="font-size: 11.0pt; font-family: 'Aptos',sans-serif; mso-fareast-font-family: Calibri; mso-fareast-theme-font: minor-latin; mso-bidi-font-family: Aptos; color: #212121; mso-ligatures: standardcontextual; mso-ansi-language: EN-US; mso-fareast-language: SV; mso-bidi-language: AR-SA;" lang="EN-US">Extracting Fission observables in solenoidal spectrometers&nbsp;
Abstract:&nbsp;
Modern subatomic physics experiments often require large accelerator facilities in order to produce and study exotic particles and isotopes. Experiments with highly segmented detectors as well as sophisticated analysis software are nowadays state-of-the-art. This project is motivated by an upcoming experiment in the ISOLDE facility at CERN that aims to study the fission barrier of 230Ac through 229Ac(d,pf) reactions. This is a first step to explore exotic neutron rich isotopes, and the role fission has in the astrophysical rapid neutron capture process (r-process).
This master thesis focuses on development and tests of the analysis software to include newly added detectors before the start of the experiment. By converting simulated data to mimic experimental data it is possible to test the analysis software in advance. Comparing the data output from the software with the same data before the conversion, allows to spot bugs in the software. Thus, the software can be prepared and tested before the experiment, as it removes the need to collect measured data. This means that the software can be used as a diagnostic tool already during the setup phase prior to the experiment.
Examiner: Andreas Heinz Supervisor: Andreas Heinz Opponent: <span style="font-size: 11.0pt; font-family: 'Aptos',sans-serif; mso-fareast-font-family: Calibri; mso-fareast-theme-font: minor-latin; mso-bidi-font-family: Aptos; color: #212121; mso-ligatures: standardcontextual; mso-ansi-language: EN-US; mso-fareast-language: SV; mso-bidi-language: AR-SA;" lang="EN-US">Hazel Ndulue
Location of presentation: <a rel="noopener" href="https://maps.chalmers.se/#24d8b7be-1f59-4388-be28-a07861b429b2" target="_blank" title="Chalmers map" data-anchor="#24d8b7be-1f59-4388-be28-a07861b429b2">PJ-salen</a>

Title of thesis:&nbsp;Fuel cell catalyst coating quality for reliable ORR activity results
Abstract: Proton exchange membrane fuel cells (PEMFCs) are energy conversion devices that could play a key role in the reduction of greenhouse gas emissions. However, one major problem for PEMFCs is the slow oxygen reduction reaction (ORR), which causes large overpotentials and requires a large amount of expensive platinum catalyst to be sped up. For that reason, evaluation of the ORR activity of catalysts is important, and the rotating disk electrode (RDE) method is commonly used for this purpose. However, there are still problems with achieving reliable results of the ORR activity with RDE, specifically due to the activity’s dependence on the quality of the catalyst coating on the electrode. This thesis investigates how different parameters of a catalyst ink influence the catalyst coating and how to achieve a uniform thin coating. For one catalyst, inks with different alcohol contents and platinum loadings were tested, and for a second catalyst, different alcohol contents and pH levels were tested. The alcohol content did not appear to have a significant impact on the ORR activity or the homogeneity of the thin films. A high alcohol content facilitated the spreading out of the ink thanks to a lower surface tension, but it was also harder to keep it from spreading outside the electrode disk. With platinum loading, there seemed to be a lower limit between 10 and 20 μgPt/cm2 for the catalyst to cover the entire disk homogenously. Below this limit, the mean specific ORR activity was about 20 % lower. At 34.8 μgPt/cm2, the results were about the same as for 20 μgPt/cm2, meaning no upper limit appears to have been reached. For the second catalyst, stability issues were observed, which did not significantly change with the alcohol content. Increasing the pH of the ink by adding KOH improved ink stability, but it was still not possible to produce a completely homogeneous coating. Further investigations on how to achieve a homogeneous coating with this catalyst are therefore needed.
Examiner: Björn Wickman Supervisor: Marika Männikkö Opponent: William Colliander
Location of presentation: <a rel="noopener" href="https://maps.chalmers.se/#96de5091-96fe-4e70-8def-1faa831680ae" target="_blank" title="Chalmers Map" data-anchor="#96de5091-96fe-4e70-8def-1faa831680ae">Raven &amp; Fox</a><a rel="noopener" href="https://maps.chalmers.se/#24d8b7be-1f59-4388-be28-a07861b429b2" target="_blank" title="Chalmers map" data-anchor="#24d8b7be-1f59-4388-be28-a07861b429b2"></a>

Title of thesis:&nbsp;Establishing rheological methodology and analyzing data for PEMFC catalyst ink &nbsp;
Abstract:The shift toward cleaner, low-emission energy solutions are pacing up and hydrogen powered Proton Exchange Membrane Fuel Cells (PEMFCs) are emerging as one of the leading technologies driving this transformation. Catalyst ink is a key component of membrane assembly in the PEMFC, which is composed of platinum based catalyst particles supported on carbon and an ionomer. Composition of catalyst inks, preparation, dispersion, application of catalyst layers and storage largely affect the PEMFC performance. In this study, catalyst inks of varying compositions were tested using the rheometer. Different types of rheology tests were conducted on catalyst inks samples to understand the viscous-elastic responses and their possible impact during electrode coating application. &nbsp;Ionomer to Carbon (I/C) ratio of the catalyst powder was noted to be the main factor in bringing stable viscosity response under shear conditions for the catalyst ink. Solid content follows as a second important factor, however combination of higher I/C ratio with 45-60% content of N-Propanol (NPA) as solvent responds well during the oscillatory sweep tests results. Catalyst ink of such composition shows dominant elastic modulus, higher relaxation time and cross over point (Elastic Modulus G’= Loss Modulus G’’) with stable behavior in linear visco-elastic region (LVER) region. Furthermore, the key parameter Deborah (De) was found to be close to 1 for the best performing catalyst inks, which in rheology is used to characterize the fluidity vs. elasticity of a material under deformation or flow. These findings are also validated and supported by similar results obtained from subscale testing of these CIs membrane assemblies. While these tests and analysis helped make headway in initial understanding of catalyst inks used at PowerCell Group, more research work is needed to understand morphology correlation and response of particle interactions at the nano scale using advanced techniques like cryo-TEM, SEM and SAXS.
Examiner: Björn Wickman Supervisor: Marcus Liljenberg Opponents: Lorensu Hewa Welle Kamkanamge Sujith Priyantha
Location of presentation: <a rel="noopener" href="https://maps.chalmers.se/#96de5091-96fe-4e70-8def-1faa831680ae" target="_blank" title="Chalmers Map" data-anchor="#96de5091-96fe-4e70-8def-1faa831680ae">Raven &amp; Fox</a>

Title of thesis: Advancing Sub-Visible Particle Characterization in Inhaled Biologics
Subtitle:&nbsp;Micro-Flow Imaging for Particle Analysis and Sub-Population Differentiation
Abstract: Protein aggregation poses a significant immunogenicity risk in inhaled biologics, where aggregated proteins may trigger adverse immune responses. Conventional methods, such as Light Obscuration, are used to quantify sub-visible particles, but often face challenges in detecting small and translucent particles.
This thesis explores how continuous flow microscopy, specifically Micro-Flow Imaging, can be used to differentiate particle sub-populations by analyzing morphological and optical data. Drug products and excipients are examined to identify and quantify these sub-populations, their composition, aiming to enhance the understanding of the particulate environment in the formulations.
The results reveal that different formulations exhibit particles with distinct characteristics. Particle distributions have been established, resulting in unique profiles that could potentially be used to identify the presence of specific formulations in unknown samples. However, a deeper understanding of the interactions and complexities among various substances in the formulations is necessary to enhance the accuracy of the identification test.
Examiner: Jan Swenson Supervisors: <span style="font-size: 12.0pt; font-family: 'Aptos',sans-serif; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: Aptos; mso-ansi-language: SV; mso-fareast-language: SV; mso-bidi-language: AR-SA;">Noemi Gaglianone, Gerard Masdeu Opponent: <span style="font-size: 12.0pt; font-family: 'Aptos',sans-serif; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: Aptos; mso-ansi-language: SV; mso-fareast-language: SV; mso-bidi-language: AR-SA;">Olivia Jonsson
Location of presentation: <a rel="noopener" href="https://maps.chalmers.se/#24d8b7be-1f59-4388-be28-a07861b429b2" target="_blank" title="Chalmers map" data-anchor="#24d8b7be-1f59-4388-be28-a07861b429b2">PJ-salen</a>

Title of thesis: From magnetic field seed generation to dynamo in collisionless plasmas
Abstract: The origin of the cosmic magnetization present throughout the universe, greatly impacting the development of a diverse set of astrophysical systems, has long been a subject of research. Observations of cosmic magnetic fields, for example in the weakly collisional intracluster medium, show field magnitudes consistent with having been produced through the dynamo process, which causes small seed magnetic fields in plasmas to grow exponentially through the conversion to magnetic energy from kinetic energy in turbulent flows. Magnetohydrodynamics, the standard method of modeling dynamo, is not valid for weakly collisional systems since it assumes that a high collisionality dominates over competing small-scale processes, such as magnetic field seed-generating plasma instabilities. However, a fully kinetic treatment of the problem in electron-proton plasmas is prohibitively expensive numerically.  
In this thesis an advanced collisionless fluid plasma model, with a complexity between that of magnetohydrodynamics and a kinetic model, is used to study magnetic field growth in a plasma in the presence of driven turbulent flows. A significant decoupling of the ion and electron dynamics is observed for the employed mass-ratio, allowing access to previously unexplored physics. The simulations demonstrate both the dynamo process and magnetic field seed generation through the electron Weibel instability. The fluid and magnetic Reynolds numbers, key quantities in classical dynamo theory, are generalized for a collisionless system. This is done by studying the dependence of flow and magnetic energy damping rates on the strength of the pressure isotropization encoded in the ion and electron heat flux closures of the fluid model. A scan over the effective magnetic Reynolds number is performed for the dynamo simulations by adjusting the strength of the electron closure. Strong pressure isotropization from the closure leads to behavior of the magnetic field growth expected from classical dynamo theory, whereas a small isotropization results in seed generation from pressure anisotropy-driven instabilities dominating, as previously observed in kinetic simulations of electron-positron plasmas. 
Examiner: Istvan Pusztai Supervisor: Istvan Pusztai Opponent: Liam Antonsson 
Location of presentation: <a rel="noopener" href="https://maps.chalmers.se/#7241f650-27c9-11ef-a21b-017390dd2bcd" target="_blank" title="Chalmers maps" data-anchor="#7241f650-27c9-11ef-a21b-017390dd2bcd">Eva von Bahr</a>
Online: <a rel="noopener" href="https://chalmers.zoom.us/j/62452572114?pwd=daFN9pigWaUHkDRRGGsavI9lqzEoPN.1&amp;from=addon" target="_blank" title="Zoom" data-anchor="?pwd=daFN9pigWaUHkDRRGGsavI9lqzEoPN.1&amp;from=addon">Zoom</a>

Title of thesis:&nbsp;Electromagnetic modeling of the effect of plasma sheath on radar signatures of hypersonic targets
Abstract: Hypersonic missiles have been suggested to have significantly different radar signatures compared to similar slower vehicles. This has been attributed to the plasma sheath that forms when high-temperature air in the hypersonic shock front partially ionizes air molecules. Under certain conditions, the free electrons in this plasma can absorb electromagnetic radiation. It is unclear whether this effect could dampen the scattered radiation from targeted hypersonic missiles, effectively making them stealthy to radar. However, the physics of plasma-induced stealth of hypersonic vehicles is quite complex, involving the spatial distributions of plasma and electron–neutral collision frequencies as well as the microwave frequency. For this reason, broad claims about the stealth of hypersonic vehicles must be supported by accurate numerical simulations. In this thesis, the effects of a thin plasma sheath have been studied in various settings and geometries with the aid of electromagnetic as well as hydrodynamic simulations.
The ability of a plasma to shield rough surfaces, which otherwise have a large radar signature, was investigated by simulating the electromagnetic wave scattering of a plasma-covered metal slab with surface roughness in a 2D geometry. Somewhat unexpectedly, the plasma did not behave like a mirror for low frequencies and when the radiation was expected to be attenuated it was instead amplified. Additionally, the ability of the plasma sheath to distort scattered electromagnetic waves was studied analytically. The distortion was exaggerated in this simple model compared to a real-world scenario, but still it was negligible for almost every frequency. Therefore the distortion can be neglected. Finally, to study the effect of a plasma sheath with a realistic plasma density, the plasma frequency and collision frequency distributions were computed for a metal sphere flying at speeds of 3-5 km s−1 in an ambient pressure representative of a 40 km altitude. While the calculated radar signature has a limited accuracy below 1 GHz, we can conclude that in that frequency range the presence of the plasma sheath can either increase or reduce the radar signal, depending on the frequency. At some frequencies the decrease was as large as 10 dB. Our results also indicate that the plasma sheath only has minor effects on the radar signatures of hypersonic vehicles traveling below 3 km s−1, for the microwave bands above 1 GHz.
Examiner: Istvan Pusztai Supervisor: Andréas Sundström&nbsp; Opponent: Nils Müller
Location of presentation: <a rel="noopener" href="https://maps.chalmers.se/#7241f650-27c9-11ef-a21b-017390dd2bcd" target="_blank" title="Chalmers maps" data-anchor="#7241f650-27c9-11ef-a21b-017390dd2bcd">Eva von Bahr</a>
Online: <a rel="noopener" href="https://chalmers.zoom.us/j/68504068099?pwd=ajUWKmwdOePpW61PhdKhSUzA2gBnxq.1&amp;from=addon" target="_blank" title="Zoom" data-anchor="?pwd=ajUWKmwdOePpW61PhdKhSUzA2gBnxq.1&amp;from=addon">Zoom</a>

Title of thesis:&nbsp;Kinetic simulations of the proton-alpha instability in collisionless shocks
Abstract: The solar wind is a dynamic stream of collisionless plasma originating from the Sun. When it reaches the Earth's magnetosphere, it abruptly slows down from super-Alfvénic to sub-Alfvénic speeds, creating a bow shock. This compresses and heats the inflowing plasma. The solar wind consists primarily of electrons, protons and alpha-particles, which interact differently with the shock. A relative drift between protons and alpha particles develops, which can trigger a streaming instability, driving waves. Such waves have previously been identified in spacecraft observations. The dependence of the instability on the particle species temperature, density, and flow velocity has previously been investigated using the dispersion relation for an unmagnetized plasma.
In this work, we investigate this proton-alpha streaming instability using two-dimensional fully kinetic Particle-In-Cell simulations. This approach offers the flexibility to freely choose the initial conditions while simulating the full non-linear dynamics. We study the parametric dependence of the instability on the flow velocity of the alpha particles, the density ratio of the ions as well as the influence of a background magnetic field. In particular, we want to quantify the heating of different particle species due to the instability. Additionally, we aim to test the applicability of the simplified linear theory.
Our simulations show that the instability mediates a strong energy exchange from the flow speed of the alphas into plasma heating of the ions. We attribute this to a Landau resonance between the proton and the alpha distribution, which produces large plateaus in velocity space. The electron dynamics do not change significantly. The wave properties are consistent with the linear theory when the external magnetic field is small. Generally, the angle between the wave and the drift direction increases with the flow speed. The fraction of energy converted to plasma heating reaches a maximum at a wave angle of 45 deg to the drift direction. Overall, the existence of a background magnetic field slightly suppresses the instability, due to the magnetization of electrons. We conclude that the proton-alpha streaming instability can play an important role in heating proton and alpha particles across collisionless shocks.
Examiner: Istvan Pusztai Supervisor: Konrad Steinvall Opponent: Lise Hanebring
Location of presentation: <a rel="noopener" href="https://maps.chalmers.se/#7241f650-27c9-11ef-a21b-017390dd2bcd" target="_blank" title="Chalmers maps" data-anchor="#7241f650-27c9-11ef-a21b-017390dd2bcd">Eva von Bahr</a>
Online: <a rel="noopener" href="https://chalmers.zoom.us/j/66511118346?pwd=AyVGa5AHrnmCp7uK4e1VmtJE55NhQv.1&amp;from=addon" target="_blank" title="Zoom" data-anchor="?pwd=AyVGa5AHrnmCp7uK4e1VmtJE55NhQv.1&amp;from=addon">Zoom</a>

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Presentation of master thesis

Master thesis presentations at Physics

May 12 2025

10:00- 11:00 Johanna Vestgöte Norell & Fabian Kaneby, MPDSC

May 21 2025

10:00- 11:00 Tim Pagrell, MPPHS

11:00- 12:00 Jennie Berndtson, MPMED

May 26 2025

13:15- 14:00 Linus Kullmyr & Emily Blixt, MPCAS

15:00- 16:00 Marcus Hansen, MPCAS

May 27 2025

13:00- 14:00 Hampus Hansen, MPPHS & Theodor Hansson, MPCAS

June 2 2025

13:00- 14:00 Andreas Erlandsson, MPPHS

14:00- 15:00 Simon Dovrén, MPPHS

June 3 2025

9:00- 10:00 Björn Johansson, MPPHS

10:00- 11:00 Hugo Mårtensson, MPPHS

11:00- 12:00 Ahsin Hafeez, MPSES

13:00- 14:00 Sophie You, MPMED

June 10 2025

13:00- 14:00 Lise Hanebring, MPPHS

14:10- 15:10 Liam Antonsson, MPPHS

15:20- 16:20 Nils Müller, MPCAS