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Investigation and optimization of photonic molecule microcombs with low repetition rates
(2025) Dzieia, Nora
Frequency combs are a key technology for many applications, such as optical clocks,
precision spectroscopy, and wavelength division multiplexing (WDM) in optical communications.
Integrated frequency combs leveraging the Kerr nonlinearity can operate
with milliwatt-level pump powers, though their conversion efficiency (CE) typically
remains below 10%. In recent years, photonic molecules have been introduced
to overcome the problem of generally low CE observed in microcombs. Reported
efficiencies have exceeded 50% by transitioning from single cavities to photonic
molecule configurations. To date, these levels of CE have only been demonstrated
for microresonators with an FSR of 100 GHz. For low FSR photonic molecules, this
improvement is challenging due to higher intrinsic losses and a power distribution
across a larger cavity volume. In this thesis, we used Ikeda map-based simulations
to identify critical design parameters for achieving higher CE in low FSR configurations.
We characterized existing chips and compared measured comb spectra with
simulations to extract key parameters and quantify the currently achievable CE for
different FSRs. This data was used to analyze the influence of multiple parameters
on the CE, including coupling factors, input power, and comb detuning. Based
on these investigations, we developed improved parameter sets for microresonators
with repetition rates of 25 GHz and 50 GHz. The simulated CE increased from 25%
(simulation of existing devices) to over 45% for the 25 GHz design. For the 50 GHz
design, we present a parameter set that achieves a CE of over 65%. These CE values
can be achieved over a range of commonly used input powers in the milliwatt
regime. Our results demonstrate the potential to design photonic molecules with
tailored FSRs, enabling greater flexibility across applications.
Design and Simulation of a Microcontroller-Based Class D Power Amplifier for Piezo-electric Actuators in Bone ConductionHearing Aids
(2025) Remnesjö Bergstrand, Albin; Johansson, Emil
Conventional linear audio power amplifiers have been and continue to be popular
in audio applications. In recent years, digital Class D switching power amplifiers
have increased in popularity, as the demand for smaller and more efficient electronic
devices has surged. Continuous technological advances have further improved audio
quality and allowed for smaller and more efficient Class D amplifiers. One audio
technology that uses Class D amplifiers is bone conduction hearing aids. These
systems generally consist of an extrinsic microphone and sound processor, connected
to a percutaneous device with the purpose of generating sound through vibrations
to the skull bone. Historically, bone conduction devices have been designed and
operated based on electromagnetic principles using electromagnetic actuators. Over
time, a more efficient type of actuator is increasing in popularity, one that utilizes
the piezoelectric force. Low-voltage Class D amplifiers are often only available in
integrated circuits (ICs), which take a long time to develop and can be a bottleneck
in the process. This thesis explores an alternative approach by developing a design
and simulation framework for a low-voltage Class D power amplifier using discrete
components to drive a piezoelectric actuator load. The following approach aims
to reduce the development time while showcasing the feasibility of constructing
low-voltage Class D power amplifiers utilizing discrete components for piezoelectric
actuator loads, achieving performance comparable to integrated solutions. A Class
D amplifier, using a H-bridge power stage, with ΔΣ to BD PWM with dead-time
control, has been developed in simulation and with PCB design. The amplifier,
operating across the audio frequency range (20 Hz to 20 kHz), achieved a peak SNR
of 69.32 dB and a THD+N peak of 0.15% when driven with a 0.658 VRMS sinusoidal
input with a fundamental frequency of 4410 Hz. A peak apparent efficiency of 86.4%
was observed with an input voltage of 2.44 VRMS. Compared to IC designs reported
in technical literature and found in commercial products, the results are promising.
Thus, the conclusion is that the idea of designing a low-voltage discrete Class D
amplifier for piezoelectric hearing aids is deemed viable. Still, its performance could
be greatly improved by incorporating gate drivers, a higher-order ΔΣ modulator,
and more refined filter designs.
Modeling the effect of guanidinium in hybrid halide perovskites
(2025) Dahlgren Blumenau, Rickard
advancing
solar cell technologies. However, they face many issues especially related
to stability, since in general they easily degrade into photo-inactive phases due to
environmental factors like temperature, humidity and light. It is thus of interest
to understand the phase behaviors of these systems to be able to engineer stable
perovskite solar cells with favorable optoelectronic properties. Two of the most
promising organic halide perovskites for solar cells are MAPbI3 (MAPI) and FAPbI3
(FAPI). By mixing these it is possible to tune the optoelectronic properties and
phase behavior. In recent studies it has been shown that incorporating GUAPbI3
(GUAPI) could further improve the optoelectronic properties by for instance increasing
the charge carrier lifetime. However, the exact phase behaviors of these
systems have not been investigated extensively. Thus, in this thesis the temperature
dependence of the phase behaviors of mixed (MA,FA,GUA)PbI3 as well as each
pure systems were investigated by training a neuro evolution potential (NEP) model
on structural properties calculated through density functional theory (DFT). The
model predicted the previously known phase behaviors of FAPI and MAPI. Additionally,
the morphotropic phase boundary (MPB) between MAPI and FAPI was
found around 21% of FAPI, which is in agreement with previous studies. GUAPI
was found to adopt the a−a−a− phase at temperatures below 280K. Furthermore,
it was found that adding GUAPI to (MA,FA)PbI3 the MPB shifted towards higher
FAPI concentrations.
Optimizing Night Driving Simulations: A Comparative Study of Light Simulation Software
(2025) Liang, Lanyu
Night driving simulations are essential tools for the development and validation of advanced automotive lighting systems. These simulations require not only photometrically accurate representations of light-material interactions but also real-time performance suitable for iterative design and driver-in-the-loop evaluations. This thesis presents a comparative study of three rendering platforms: Ansys AVxcelerate Headlamp, Synopsys LucidDrive, and Unity, to assess their capabilities in simulating nighttime driving environments with high visual fidelity.
The study benchmarks these tools across several dimensions, including rendering performance, photometric accuracy, and perceptual similarity, using standardized test scenes and real-world photometric profiles. A particular focus is placed on evaluating Unitys real-time ray tracing capabilities, enhanced by ReSTIR, against the more static and proprietary pipelines of AVxcelerate and LucidDrive. Experiments utilize standardized test scenes and automotive-grade models under controlled nighttime conditions, profiling performance via structural similarity of rendering results, GPU utilization, frame rate, and memory consumption.
The results underscore the limitations of commercial tools in handling dynamic lighting scenarios and complex BRDFs, while highlighting the flexibility and performance of open rendering frameworks. This work provides a reproducible benchmarking methodology and lays the foundation for future research on hybrid rendering strategies, perceptual validation models, and real-time simulation of intelligent headlight systems.
Bridging Trust and Design of a Multi-Agent LLM-Based HR Chatbot: For the Times They Are A-Changin’
(2025) Axetorn, Jonatan; Edholm, Felix
Introduction: The integration of Large Language Models (LLMs) into workplace systems presents significant opportunities, particularly in the domain of human resources (HR), where repetitive tasks—such as providing information that employees could retrieve themselves—are common and could potentially be replaced by an LLM-based solution. However, a lack of user trust remains a major barrier to the adoption of LLM-based systems.
Objective: This thesis investigates what trust factors exist in LLM-based systems and how they can be addressed by system design, with a specific focus on a multiagent HR chatbot.
Method: Using a Design Science Research methodology, the study was conducted in two iterative cycles. Cycle I identified trust factors through literature review and interviews with six employees at a multinational company. It also included a workshop with five AI experts to discuss and validate design choices. Cycle II involved implementing, and evaluating an artifact, a multi-agent chatbot tailored to HR queries.
Findings: Thematic analysis revealed external trust factors: transparency, organisational measures, and external security and internal trust factors: internal security, model differences, risk of bias and reliability, which emerged as the most critical trust factor. The artifact was evaluated through interviews and metrics such as answer relevancy, faithfulness, and robustness, showing consistently strong performance and broad user acceptance.
Conclusion: The multi-agent HR chatbot effectively addressed key trust concerns and was positively received by most interviewees, demonstrating its potential for real-world application. These findings suggest that trust factors can be meaningfully addressed through thoughtful design and should be treated as a core consideration throughout the development process of LLM-based systems.
