Population ageing is increasing the need for home-based care while the available care workforce remains limited, creating a need for unobtrusive systems that support routine observation without adding tasks for elderly residents. This thesis presents the design, implementation, and validation of a concept demonstrator for a remote health monitoring system built around a smart mirror and modular sensor printed circuit board. The system measures presence, heart rate, respiratory rate, environmental conditions, and ambient light using radar and supporting sensors. A resident-facing mirror display presents the most relevant information with large visual elements, limited text, and a traffic-light interpretation scheme, while requiring no active user input. Sensor readings are published over an encrypted, certificate-based local communication link to a broker hosted on the tablet behind the mirror. A gateway subscribes to these readings, buffers them during outages, converts vital-sign data into standard healthcare observation resources, and forwards them to a reference healthcare server. Validation showed that the access-control design confined devices to their own data paths and rejected unauthenticated connections, while the custom circuit board and sensor interfaces were brought up successfully. The vital-sign radar followed expected physiological trends, although heart-rate readings showed a systematic overestimation and breathing-rate readings were closer to the reference. The project demonstrates a secure path from ambient home sensing to a healthcare information interface, but further work is needed on clinical-grade validation, production endpoint authentication, deployment hardening, and resident identification. ... Read more

The CNT-SiC composite material has in the past been demonstrated to be useful for high-aspect-ratio MEMS devices for harsh environments. This work explores the possibility of combining these MEMS devices with SiC active devices on the same wafer to create smart sensors. The fabrication process was not successful. This work exposes where further work is required, and it proposes modifications to the fabrication process to make it simpler and more robust for future attempts. Moreover, it finds that the release step of CNT-SiC devices is prone to the release of anchor points. It is theorized that this may be caused by the etchant diffusing through the porous CNT-SiC structure. This work also explores various parameters related to the CNT-SiC material. ... Read more

This thesis presents the design, manufacturing, and characterisation of a multimode metal oxide-based gas sensor. The aim of the multimode sensor is to enhance selectivity by integrating a chemiresistive sensor with a quartz crystal microbalance (QCM) into a single microscale device. The motivation for this work is the limited selectivity of low-cost gas sensors compared to laboratory systems, while the proposed design maintains the ambition of low-cost fabrication, small size, and industrial applicability. The proposed sensor combines interdigitated chemiresistive electrodes, a quartz resonator, platinum heaters, temperature-sensing functionality, and a metal-oxide-sensitive layer into a single device. The design is supported by analytical calculations and thermal simulations, after which the sensor is manufactured using standard MEMS-compatible processes, including lithography, lift-off metallisation, TEOS deposition, metal oxide printing, and packaging.

The fabricated sensor is characterised using a platinum-doped SnO2 sensing layer and a sequential electrical read-out of metal-oxide resistance and resonance frequency. The chemiresistive mode shows the strongest performance, including VOC-1 detection and an estimated limit of detection. The QCM sensor shows a resonance frequency of approximately 7.67 MHz at 50 °C and a Q-factor of about 550, but its performance is limited by low resonance quality and a relatively high detection limit. Nevertheless, combining both sensing principles yields gas-dependent relations between chemiresistive sensitivity and frequency response for VOC-1, VOC-2, and VOC-3. This demonstrates that the monolithic multimode concept provides additional discriminatory information compared with either sensing principle individually. It is concluded that monolithic integration of a chemiresistive and QCM sensor can enhance selectivity, but further optimisation of the resonator design, measurement electronics, and thermal control is required before the concept can be used as a robust, selective detector at low concentration levels. ... Read more

Magnetic-aided navigation using unmanned aerial vehicles (UAVs) is a promising method in case traditional navigation methods fail, but aeromagnetic platform noise from electric motors, electronics, and actuators can mask subtle geological signals. Traditional compensation methods, such as the Tolles-Lawson (TL) model, assume linear relationships between platform orientation and platform noise, failing to capture complex, time-varying disturbances from dynamic onboard systems. Existing machine learning approaches typically require noise-free reference measurements or known anomaly maps, resources often unavailable in practical surveying scenarios.

This thesis develops data-driven, reference-free methods for compensating platform noise in aeromagnetic measurements. The research addresses two key questions: whether deep learning methods can effectively predict and compensate platform noise without ground-truth references, and which drone subsystems contribute most significantly to platform noise.

A validation apporoach was implemented using flight data where crustal anomalies are naturally attenuated, enabling reference-free performance assessment. Comprehensive data from a fixed-wing UAV equipped with scalar and vector magnetometers, logging 273 platform-related input signals during figure-of-merit manoeuvres over an 800~m $\times$ 800~m survey area was used.

The compensation approach employed hierarchical modelling: Extended Tolles-Lawson (ETL) compensation incorporating drone inputs projected onto the magnetic field direction, followed by multilayer perceptron (MLP) neural networks trained to predict residuals. SHAP (SHapley Additive exPlanations) analysis provided model-agnostic feature importance assessment to identify the most influential platform inputs.

Results demonstrate substantial improvements over traditional methods. ETL compensation achieved improvement ratios averaging 7.31 for scalar magnetometers and 18.76 for vector magnetometers, compared to 4.90 and 10.19 respectively for standard TL compensation. The combined ETLNN approach (ETL + neural network) further enhanced performance to average improvement ratios of 8.87 on total field magnetometer and 22.22 on vector magnetometer data, a significant improvement over traditional TL methods.

SHAP analysis revealed that engine-related parameters (battery current, throttle commands), inertial measurement data (accelerations, gyroscopic rates, vibration), and attitude information (roll, pitch, yaw) are the primary contributors to platform noise. Features projected onto the magnetic field direction consistently outperformed raw inputs, validating the physical basis for this transformation, while derivative features contributed minimally whilst increasing overfitting.

The primary limitation is the inability to validate performance on data containing actual magnetic anomalies, as the high-altitude validation approach deliberately suppressed geological signals. Future work should prioritise validation using artificial magnetic sources or reference magnetometer configurations to assess preservation of genuine geological signals.
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Organic electrochemical transistors (OECTs) are a promising technology in the field of bioelectronics. They bridge electronics and biology through their ability to operate in aqueous environments. Their ability to transduce biological signals into electronic ones makes them a preferred choice for bioelectronic applications, such as biosensing and neural interfaces. While p-type materials like PEDOT:PSS have become the benchmark for the OECT performance, the development of stable, high-mobility n-type channel materials remains a major challenge. These materials are often limited by poor air stability, low electron mobility, and restricted ionic transport. In this work, a newly developed semiconducting n-type polymer with cleavable side chains is investigated. The polymer, YYBC, undergoes a post-deposition thermal treatment, which leads to a porous, more hydrophilic polymer, YYAC. This cleaved version aims to improve the performance of an n-type OECT.
The research followed three main objectives. OECT devices were first fabricated in a cleanroom environment, then a measurement setup for steady-state and transient characterization was developed, and lastly, the new n-type polymer was evaluated. For device fabrication, standard microfabrication methods were employed. For the measurement setup, programmable source-measure units, a function generator, and an oscilloscope were controlled through MATLAB for data acquisition and analysis. Lastly, the performance of the n-type polymer was assessed using electrochemical and electrical characterization. Parameters such as volumetric capacitance, transconductance, and time response were evaluated.
Results of this work show that the post-deposition side-chain removal significantly improves the polymer’s electrochemical behaviour. The findings show improved performance metrics, indicating that the new n-type polymer can be a promising material for future OECT applications. ... Read more

Traditionally lithium-ion batteries (LIBs) use graphite as the anode material because it is very stable and has a very well understood insertion/extraction lithiation mechanism. These batteries are used in many applications around the world due to the high power-energy ratio of these batteries when compared to most other modern chemical batteries. The maximum theoretical capacity of graphite is 372 mAh/g, which works decently for most applications, and it is stable enough to last well over 1000 charge-discharge cycles before significant capacity loss. This has been a standard for many years, but with increasing demand for higher energy
density battery applications that can last longer between charging cycles and some concern in the mining and refining of graphite, new materials are being investigated and silicon is a promising contender. Silicon has a theoretical capacity of 4200 mAh/g as an anode in lithium ion batteries, but is much less stable and often has significant capacity loss after 100 or fewer cycles. This is due to the material swelling between 200-300% of its initial volume when lithiated, causing several forms of degradation to occur much faster than in graphite anodes. A potential solution to this issue is using a silicon sub-nitride (SiNx) anode material, which
has been shown experimentally to have capacities on the order of 1500+ mAh/g and higher stabilities of 200- 300 cycles or more. There is room for improvement before these batteries can rival those with graphite anodes, but this thesis aims to move one step closer to bridging this gap and making silicon-nitride anodes commonplace in lithium ion batteries. Compared to graphite, silicon is a very abundant element with a massive amount of research and industry already in place that could potentially aid in making these anodes more readily available on a large scale. In this work, plasma enhanced chemical vapor deposition (PECVD) is used to deposit layers of silicon and silicon nitride with varying compositions and mass loadings onto textured copper foil current collectors that are then made into anodes in LIBs. PECVD is an effective and scalable technology, allowing for high precision control over deposition conditions of thin films. The composition of the film is determined by the flow rate ratio of the precursor gases silane and ammonia that are then ionized together to deposit SiNx onto the foil. Physical
and electrochemical analyses are then performed to determine the specific compositions of these materials and address how these two parameters affect their electrochemical performance as anodes. After thorough testing is done, a final objective is explored by looking into how using a thin layer of the most stable SiNx on top of a layer of pure silicon might improve battery performance as an artificial solid electrolyte interface (SEI). Three different deposition times of 30 minutes, 1 hour and 1.5 hours along with five flow rate ratios (roughly)
corresponding to pure Si, SiN0.2, SiN0.4, SiN0.6 and SiN1.1 were used to create fifteen different sets of anode material. These materials were tested physically to determine the chemical composition and mass loading of the material, then tested as anodes to determine their specific capacities and stability in batteries. It was found that the lower mass loadings corresponded to higher specific capacities and more stable anodic performance, and the most stable materials for the lowest mass loadings were SiN0.4 and SiN0.6 with average specific capacities of 2204.7 mAh/g and 1135.6 mAh/g and capacity retention of 105% and 117% over 100 cycles, respectively.
The bi-layer depositions made with the SiN0.6 as a thin top layer did not perform as well as the pure SiN0.6 anodes, leading the author to recommend research into other methods of enhancing battery performance. ... Read more

Magnetic sensors play a crucial role in various fields. The 3-D magnetic field sensing capability is becoming increasingly important in applications such as navigation, position detection and consumer electronics. The final goal of this work is to design an analog front-end circuit to read out a novel 3-axis Hall magnetic sensor at the transistor level. The design of the IC front-end is an extension of the PCB characterization of the Hall sensor. In this work, a PCB (printed circuit board) is designed first for the characterization of the sensor. The measured specs are used for the IC front-end design. Finally, this current spinning read-out system achieves a residual offset of 1 mT and a dynamic range of 58 dB. ... Read more

Microwave Induced Plasma (MIP) is an advanced decapsulation tool developed by Jiaco Instruments. The goal of this thesis is to optimise the current MIP system. There are two directions: 1. Improve the etching rate. 2. Find selectivity between different materials (Si, SiO2, SiN). The experiments are divided into two parts in total, improved cavity and CF4-based MIP machine etching selectivity experiment. The cavity experimental results demonstrate that high input power is the route to optimising MIP efficiency. Etch experiments demonstrate that the CF4/O2 gas recipe is effective in achieving etch selectivity and that temperature is a key factor influencing these etch selectivities. ... Read more

In the context of designing a real-time brain-computer interface for playing a game using the OpenBCI Ultracortex "Mark IV" headset, this paper focuses on the work of the decoding subgroup. The primary responsibility is to analyse EEG data retrieved from the OpenBCI headset and classify the intention of the user. Our objective is to achieve a high-accuracy classification of the EEG signals. The paper is structured into three main sections: preprocessing, feature extraction, and classification. Multiple methods for preprocessing and classification of motor execution EEG signals will be analysed, striving to contribute to the real-time implementation of the project. The results of our work provides valuable insights for future research and development in this field. ... Read more

As silicon carbide(SiC) gets more and more attention from the semiconductor industry due to its robust mechanical and chemical properties, reliable and standardized processing technologies such as reactive ion etching(RIE) for SiC are in great demand. This is because of the difficulty and challenge of fabricating micro devices on the SiC substrate. Although the high hardness and chemical inertness make SiC a good candidate for applications such as sensors in harsh environments, they also impede the development of SiC-based devices when considering processing. This thesis aims to develop a standardized inductively coupled plasma(ICP) reactive ion etching(RIE) process for 4H-SiC substrate etching. The developed process is expected to be applied in the fabrication of micro-electro-mechanical systems(MEMS). The specifications are a high etch rate, micro-masking-free surface, and high selectivity. First, a literature review was conducted to comprehensively study the characteristics of the SiC material and the mechanisms of the ICP RIE process. Second, a baseline recipe was developed guided by the theory studied in the literature works. Third, initial tests were conducted, and the preliminary optimizations with a focus on etch rate and micro masking suppression were performed. Fourth, the design of experiments(DOE) based on the preliminarily optimized recipe was conducted to study the effect of process parameters on etch rate, etch profile, and selectivity. Last, the optimized recipes with a focus on etch rate, etch profile, and selectivity were summed and listed. The achieved maximum etch rate was 1.26 µm/min. The maximum selectivity of the hard mask material to SiC was 153 when the nickel hard mask was used. Amicro-masking-free surface of SiC was achieved. ... Read more