This thesis presents a self-powered adaptive piling-up rectifier-less synchronized switch-harvesting-on-inductor (APReL-SSHI) interface for piezoelectric energy harvesting (PEH). The proposed interface introduces two distinct operational modes, energy transfer mode (ETM) and voltage piling-up mode (VPM), that adaptively select the optimal mode based on varying vibration excitation levels to maximize energy extraction. This adaptive piling-up mechanism effectively addresses the inherent limitation of the narrow optimal rectified voltage range (ORVR) seen in conventional S-SSHI rectifiers by enabling capacitor charging beyond standard thresholds. Experimental results demonstrate that the proposed APReL-SSHI circuit achieves up to 5.27 times the maximum output power compared to a full-bridge rectifier (FBR) and expands the ORVR by 4.16 times compared to a conventional S-SSHI circuit. Consequently, the APReL-SSHI delivers superior balance between these two key performance metrics relative to existing state-of-the-art rectifiers. Moreover, the circuit uniquely exhibits a secondary output power peak, reaching approximately 94\% of maximum power when operated above the standard maximum power point (MPP) voltage. Under constant input conditions, the voltage associated with this secondary power peak is easily adjustable, thereby facilitating direct voltage matching for diverse load requirements and achieving near-MPP tracking efficiency of 94\% without the need for an additional MPPT controller.

Piezoelectric Energy Harvesting (PEH) offers a viable and sustainable solution for powering low-power electronic systems in hard-to-reach or maintenance-intensive environments, such as those found in aviation. The focus of this thesis lies on the circuit design aspect of the system, encompassing harvesting efficiency, regulation, and adaptive switching logic. The results validate that the proposed design fulfills the energy demands of a low-power wireless sensor, even under irregular excitation patterns. A range of advanced rectifierless interface topologies are investigated, including Rectifierless Synchronous Electric Charge Extraction (ReL-SECE), Rectifierless Synchronized Switch Harvesting on Inductor (ReL-SSHI), and Parallel-SSHI (P-SSHI). These non-linear techniques are selected for their ability to maximize power output, eliminate diode thresholds, and dynamically adapt to varying load and vibration conditions, significantly improving power transfer compared to traditional full-bridge rectifiers. Energy storage is realized through the use capacitors due to their rapid charge/discharge characteristics and long operational life. To ensure circuit safety and longevity, an over-voltage protection mechanism is implemented using a shunt regulator in combination with a resistive voltage divider. Additionally, a dedicated voltage regulation stage is incorporated to maintain a stable 3.3 V DC output, necessary for reliable operation of downstream wireless transmitters and onboard sensor systems. The proposed system is designed to be energy-autonomous, capable of cold-start operation, and optimized for long-term deployment without the need for external maintenance or battery replacement. The approach aligns with current trends in micro-energy harvesting (MEH) for IoT applications, emphasizing compactness, adaptability, and robustness under real-world conditions. Overall, the system demonstrates the practical potential of intelligent, self-powered harvesting circuits in enabling sustainable sensor networks and instrumentation in modern aircraft environments.

This study presents an AlN-based Lamb wave (A0 mode) liquid sensing device designed for biomedical applications. The Lamb wave device features a 1.5 μm composite membrane consisting of a 500 nm LPCVD SiN and a 1 μm of a c-axis oriented AlN film. Additionally, an innovative 45° rotated IDT design was explored to minimize edge reflections towards the output IDT. Liquid testing experiments, involving IPA, DI water, and D-PBS, were conducted to see if the devices were able to differentiate between these liquids. Results demonstrate that the fabricated Lamb wave devices exhibit sensitivity to mass loading and can distinguish between liquids based on phase, frequency, and gain characteristics. Devices with the rotated IDT design have shown a significant increase in resonance by 15 dB, as well as enhanced sensitivity compared to those with the normal design. Furthermore, devices with the rotated design demonstrated a higher Q factor of 680, indicating superior performance over the normal design (Q factor of 450). These findings suggest that a Lamb wave device with the 45° rotated IDT design holds considerable potential for applications that demand accurate liquid characterization and detection.

This study deals with the challenge of warpage in power modules, vital components in the rapidly expanding electric and hybrid-electric vehicle industry. The variations in temperature during manufacturing, resulting in significant warpage changes, contribute to device cracks, delamination, and reduced reliability.
The primary focus is understanding and mitigating the warpage phenomenon in power module substrates. This warpage is induced by thermo-mechanical stresses during the assembly packaging process. The investigation begins by exploring the cause of warpage change by characterizing annealed copper properties and employing 2D finite element model (FEM) analysis. The study identifies plastic strain as the dominant cause of warpage change during process steps. Subsequently, a validated 3D FEM simulation model is developed to replicate practical annealing and sintering processes. Lastly, the project delves into factor analysis to identify critical variables influencing warpage. It underscores that balancing residual copper volume is crucial in warpage reduction. Additive and subtractive manufacturing techniques establish a correlation between the removal of copper volume and warpage reduction.

This project provides comprehensive insights into the manufacturing process of AMB substrate, warpage behavior, and effective strategies for reduction, constructing a solid foundation for future manufacturing and design.

Bacterial identification is crucial for addressing infectious diseases and enabling effective treatment strategies. Conventional bacteria identification methods like MALDI-TOF, while efficient, lack the capability for screening the effectiveness of antibiotics. On the other hand, existing antimicrobial resistance (AMR) tests, despite being reliable, suffer from time inefficiency and lack concurrent identification capabilities. In response to these challenges, the present study employs the recent advancements in single-cell nanomotion detection using graphene drums to address these limitations. We integrate nanomotion detection with Machine Learning (ML) algorithms which enables us to simultaneously identify bacteria phenotype and their resistance to antibiotics. Bacterial time signals are transformed into time-frequency spectrograms, which then serve as inputs for machine learning algorithms. Through pattern recognition, these algorithms identify features within the images, facilitating the development of robust classification models. Utilizing single-cell nanomotion signals, differentiation is achieved between the species Escherichia coli, Staphylococcus aureus, and Klebsiella pneumoniae, as well as in detecting antibiotic-resistant and -susceptible strains, achieving an accuracy of 98.57% in the latter. This research marks the first instance of ML integrated with nanomotion detection for bacterial species identification and antibiotic susceptibility testing. It provides a basis for advanced diagnostic tools, expediting the provision of vital data regarding bacterial identification and antibiotic susceptibility, contributing significantly to medical diagnostics.

The processes that take place within cells are complex. Single-cell analysis is a method that is employed to gain further understanding of the working mechanisms on a single-cellular level. The controlled transport of substances through the cell membrane is important for studying the behaviour and responses of single living cells. Femtopipettes are used as a means to accurately target and sample cells with high viability rates. Different actuation principles exist for femtopipettes, but pressure actuation is identified as the most versatile and straightforward method. However, the volume dosing resolution of pressure driven femtopipettes lags behind other actuation methods. Throughout literature, the minimum reported dose is identified as 100 femtolitre (1 fL= 10^-15 L), achieved by applying a pressure pulse to a femtopipette. In this work, two new concepts are proposed and researched with the goal of increasing the volume dosing resolution of pressure driven femtopipettes. A multi-scale 3D printing strategy was employed where functional femtopipettes were successfully printed using two-photon-polymerization (2PP). The first concept incorporates a physical barrier in the form of a flexible membrane into the femtopipette. It was expected that the volume actuated by the deformation of the membrane could be controlled and calibrated. The deformation of 2PP printed membranes was characterized and the achieved volume displacement was well in the desired range of 100 fL. However, tests with liquid dosing did not succeed in achieving this same range, and difficulties were experienced with reproducibility. The second concept exploited the phenomenon of capillarity by incorporating axisymmetrical phaseguides as a means to control the position of the liquid-air meniscus. Consecutive geometrical steps were created that allowed for discrete and robust control over the liquid portion within the femtopipette. Step sizes of 10 picolitre (1 pL= 10^-12 L), 200 fL and 60 fL were fabricated and successfully tested, breaching beyond the current state of the art. This concept thus demonstrates both the level of customization and the unprecedented volume dosing resolution that was achieved.

In pursuit of extremely sensitive sensors, the dimensions of these sensors get smaller and smaller. Small scale resonators are commonly used as sensors by relating changes in the dynamic behaviour to a sensed quantity. Conventionally, the dynamics used for sensing are in the linear regime. But at smaller scales the dynamic range of the linear regime decreases. Therefore, it is of interest to investigate the dynamic behaviour in the nonlinear regime, as with the decreasing scale of the resonators this becomes inevitable. Especially, little is known about the frequency stability in this region. The frequency stability is an indication for the potential sensitivity that the resonator can have as sensor. By using phase locked loop (PLL) the frequency stability around the resonance frequency of nonlinear resonators can be obtained. This research contains attempts to control multilayer graphene drums around its fundamental resonance frequency with PLL. In addition, the frequency stability at these points are presented by measure of the Allan deviation. There are roughly two different distributions of the frequency stability over the frequency response obtained. One resonator shows behaviour attributed to internal resonance. This internal resonance is linked to an increase of nonlinear damping. Combining that with a simple simulation model, a relation was found between increased nonlinear damping and an improvement of frequency stability.

The suspended microchannel resonator is one of the most reliable devices for the mass measurement of biological and chemical specimens. Since it works in vacuum, the energy dissipation is decreased to the minimum. In this case, the instability related to the thermoelastic coupling effect has become a major source of uncertainty and a main hindrance for higher mass precision. In order to explore methods to control the thermoelastic coupling effect, we investigated factors that are relevant to the instability in eigenfrequency measurements, including the thickness of metal coating on the top of the resonator, and the position of the detecting laser spot on the resonator. We found that this instability-induced error is 1 to 2 orders of magnitude lower on resonators without coating than on those with coating, and 3 to 4 orders of magnitude lower if the measurement is done with the first flexural eigenmode than with the first torsional mode. The minimum mass error is achieved when measuring the first flexural eigenmode on an uncoated suspended microchannel resonator. It is in the magnitude of zeptogram (10e-21g), and can be smaller than the minimum detectable mass change which is limited by the minimum detectable frequency change in the measurement.