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Electrostatic uniformity and two-dimensional quantum dot arrays in silicon and germanium
No full textThe spin of a single electron or hole provides an attractive candidate for implementing a quantum bit when confined in a semiconductor quantum dot. Such a spin qubit is characterized by long coherence and short gate times. High-fidelity single and two-qubit operations have been demonstrated as well. Additionally, semiconductor quantum dots have a small footprint (~ 100 nm x 100 nm) and their fabrication employs techniques similar to processes commonly used in modern semiconductor technology foundries. This promises the realization of dense qubit arrays, leverage through industrial fabrication, and direct co-integration with classical control circuits.Thus far, one-dimensional quantum dot arrays have been studied extensively. Yet, only by realizing two-dimensional quantum dot arrays the small footprint of quantum dots is fully exploited. Also, due to their small size quantum dots are extremely sensitive to their local environment and fabrication imperfections. In current devices, an individually tailored set of gate electrode voltages is required for each quantum dot to confine a single charge. The limited space available for routing these voltages on the device, coupled with the associated overhead in required voltage sources, presents a challenge in scaling quantum dot arrays, especially two-dimensional arrays.This thesis focuses on two-dimensional quantum dot arrays and gate voltage uniformity. The first part (chapter 3 and 4) reports the realization of two-dimensional quantum dot arrays in a silicon/silicon-germanium (Si/SiGe) and a germanium/silicon-germanium (Ge/SiGe) heterostructure. Afterward (chapter 5 and 6), a novel all-electric method is presented to achieve increased homogeneity of the required gate voltages.In chapter 3 a 2 x 2 quantum dot array in a Si/SiGe heterostructure is presented. It is tuned to be occupied by a single electron per quantum dot reaching the (1,1,1,1) charge state. Dedicated barrier gate electrodes on the device allow for controlling the interdot tunnel couplings between neighbouring quantum dots from about 30 ueV up to approximately 400 ueV as characterized through polarization line measurements.In chapter 4 the focus is shifted towards a more scalable gate architecture for two-dimensional quantum dot arrays. It is inspired by random access architectures that are found in classical electronics. Specifically, a 4 x 4 quantum dot array in a Ge/SiGe heterostructure with shared gate electrode voltages is introduced. In this device, an odd charge occupancy is reached with either one or three holes in all 16 quantum dots simultaneously. Also, two shared barrier gate electrodes are placed between adjacent quantum dots. These enable selective control of the interdot tunnel coupling from less than 3 GHz to more than 10 GHz.Spatial fluctuations in the electric background potential still limit the scalability of such a shared control array. Therefore, chapter 5 introduces a new method to increase the electrical uniformity in quantum dot devices. The presented method is based on applying stress voltages to the device gate electrodes. It enables the tuning of pinch-off voltages in quantum dot devices over hundreds of millivolts. Afterward, the new pinch-off voltages remain stable for hours at least. The method is used to homogenize the pinch-off voltages of the plunger gates in a linear array designed for four quantum dots. It reduces their spread by one order of magnitude from 153 mV to 20 mV.Motivated by this demonstration, in the experiment presented in chapter 6 the stress voltage tuning method is applied to control the plunger gate voltages required to reach single electron occupation in a quantum dot array. In a double quantum dot, a stable (1,1) charge state is reached at identical and predetermined plunger gate voltage and for various interdot couplings. Finally, by applying stress voltages a 2 x 2 quantum dot array is tuned such that the (1,1,1,1) charge state is reached when all plunger gates are set to 1 V.QCD/Veldhorst La
Continuous Wave Measurements Collected in Intermediate Depth throughout the North Sea Storm Season during the RealDune/REFLEX Experiments
No full textHigh-resolution wave measurements at intermediate water depth are required to improve coastal impact modeling. Specifically, such data sets are desired to calibrate and validate models, and broaden the insight on the boundary conditions that force models. Here, we present a wave data set collected in the North Sea at three stations in intermediate water depth (6–14 m) during the 2021/2022 storm season as part of the RealDune/REFLEX experiments. Continuous measurements of synchronized surface elevation, velocity and pressure were recorded at 2–4 Hz by Acoustic Doppler Profilers and an Acoustic Doppler Velocimeter for a 5-month duration. Time series were quality-controlled, directional-frequency energy spectra were calculated and common bulk parameters were derived. Measured wave conditions vary from calm to energetic with 0.1–5.0 m sea-swell wave height, 5–16 s mean wave period and W-NNW direction. Nine storms, i.e., wave height beyond 2.5 m for at least six hours, were recorded including the triple storms Dudley, Eunice and Franklin. This unique data set can be used to investigate wave transformation, wave nonlinearity and wave directionality for higher and lower frequencies (e.g., sea-swell and infragravity waves) to compare with theoretical and empirical descriptions. Furthermore, the data can serve to force, calibrate and validate models during storm conditions. Dataset: https://doi.org/10.4121/233f11ff-7804-4777-8b32-92c4606e56d8 Dataset License: CC-BY 4.0.Environmental Fluid MechanicsCoastal Engineerin
Unravelling uncertainty in trajectory prediction using a non-parametric approach
No full textPredicting the trajectories of road agents is fundamental for self-driving cars. Trajectory prediction contains many sources of uncertainty in data and modelling. A thorough understanding of this uncertainty is crucial in a safety-critical task like auto-piloting a vehicle. In practice, it is necessary to distinguish between the uncertainty caused by partial observability of all factors that may affect a driver's near-future decisions, the so-called aleatoric uncertainty, and the uncertainty of deploying a model in new scenarios that are possibly not present in the training set, the so-called epistemic uncertainty. They reflect the trade-off between data collection and model improvement In this paper, we propose a new framework to systematically quantify both sources of uncertainty. Specifically, to approximate the spatial distribution of an agent's future position, we propose a 2D histogram-based deep learning model combined with deep ensemble techniques for measuring aleatoric and epistemic uncertainty by entropy-based quantities. The proposed Uncertainty Quantification Network (UQnet) employs a causal part to enhance its generalizability so rare driving behaviours can be effectively identified. Experiments on the INTERACTION dataset show that UQnet is able to give more robust predictions in generalizability tests compared to the correlation-based models. Further analysis presents that high aleatoric uncertainty cases are mainly caused by heterogeneous driving behaviours and unknown intended directions. Based on this aleatoric uncertainty component, we estimate the lower bounds of mean-square-error and final-displacement-error as indicators for the predictability of trajectories. Furthermore, the analysis of epistemic uncertainty illustrates that domain knowledge of speed-dependent driving behaviour is essential for adapting a model from low-speed to high-speed situations. Our paper contributes to motion forecasting with a new framework, that recasts the problem of accuracy improvement in a way that focuses on differentiating between unpredictable components and rare cases for which more and different data should be collected.Transport and Plannin
Energy Flexibility in the Chemical Industry
No full textThe electrification of the production processes in the chemical industry is seen as a promising option to reduce its greenhouse gas emissions. This would result in a significant increase in the demand for electrical energy. The supply of electricity is becoming more fluctuating due to the variable nature of solar and wind energy. To ensure the stability of the grid, the consumption of electricity needs to equal the supply. Additionally, many countries are dealing with grid congestion, which means that there is insufficient transmission capacity for all consumers who want to receive power. One potential solution to these challenges is industrial demand response whereby companies adjust their electricity consumption to the available supply. The chemical industry might be able to provide this demand response through flexible operations of its production processes.The goal of this research was to investigate whether companies have concrete plans to engage in energy flexibility with their production processes, and to determine the priority level they assign to it. This included examining how widely energy flexibility is incorporated into companies’ ten-year roadmaps, identifying the obstacles to electrification in the chemical industry, and understanding the challenges of operating chemical production flexibly.To answer these questions, interviews were conducted with participants who work at chemical companies in the Netherlands. The participants were recruited by compiling a list of all chemical companies in the Netherlands and using LinkedIn to approach suitable candidates within each company with a request for an interview. Those participants who responded positively were interviewed using a semi-structured interview methodology in interviews lasting 30-45 minutes. The interviews were processed into anonymous summaries which were then used to answer the research questions.Participants from twelve different companies were interviewed, representing approximately a quarter of all companies active in the Dutch chemical industry. These companies are active in a mix of sub-sectors of the chemical industry. A possible response bias should be noted, as companies already engaged in electrification and energy flexibility may be over-represented among these twelve companies compared to the chemical industry as a whole. Moreover, as only one participants was interviewed per company, there is a significant chance of personal bias affecting the results.The results showed that flexible energy use was included in half of the twelve interviewed companies. However, it was a priority for only two companies. For the remaining four companies, flexible energy use was a side benefit of using both natural gas as well as electricity as a source for process heat in the transition to fully electrified process heat generation. Although four more companies had tentative plans for flexibility, they did not expect these to be feasible within the next ten years.The results also showed that for eight out of twelve companies, lack of sufficient grid capacity was a crucial obstacle to electrification. However, only two of those companies indicated that they would be willing to consider operating their process flexibly in return for accelerated access to the desired grid capacity. The benefits of quicker access to the grid do not outweigh the obstacles to operating flexibly for most companies. The most important obstacles were related to the high investment cost of chemical plants in the chemical industry. At this juncture, the financial benefits of demand response do not outweigh the increased investments costs needed to make flexibility possible for most companies.Management of Technology (MoT
Development and experimental evaluation of surface enhancement methods for laser powder directed energy deposition microchannels
No full textThis research evaluates Laser Powder Directed Energy Deposition (LP-DED) for producing fine feature internal microchannels. This study is focused on enhancing and characterising the surfaces of microchannels produced using techniques such as abrasive flow machining, chemical milling, chemical mechanical polishing, electrochemical machining, and thermal energy method to modify internal surfaces of microchannels made from NASA HR-1 Fe-Ni-Cr alloy. Flow testing for discharge coefficient measurement is conducted on processed microchannel samples, followed by characterisation through optical microscopy, Scanning Electron Microscopy (SEM), and Computed Tomography. Findings reveal variations in surfaces due to powder adherence, melt pool undulations, and polishing mechanisms. The study emphasises the significance of removing material equivalent to the mean powder diameter to reduce surface roughness and impact the discharge coefficient. The research proposes a ratio for planarising roughness and waviness peak height and density, offering insights for tailored surface adjustments in specific applications requiring reduced flow resistance. Highlights Internal microchannels with thin-walls were fabricated using the laser powder directed energy deposition process. Various surface enhancements and polishing processes were developed to modify the surface texture of the LP-DED channels. Flow testing was conducted to determine the discharge coefficient. Post-test characterisation was completed to obtain cross sectional area, perimeter, surface texture, and general surface condition to analyse results. Ratio of roughness and waviness peak and density (Spk/Spd and Wp/WPc) is proposed as a relevant surface characterisation parameter. Tailored surface modifications for specific end-use applications.Space Systems EgineeringAstrodynamics & Space MissionsFlight Performance and Propulsio
DESIGNING TOMORROW - The impact of generative AI on the Strategic Design Process
No full textIn the past year, generative AI has made significant leaps, making it more accessible, helpful, and known to the broader public. This technology promises to change how we work, automating repetitive tasks, generating content, and assisting in problem-solving scenarios easier. This research explores how implementing this new technology will influence the strategic design process and how strategic designers should adapt to get the most out of the technology. As a result, a guidebook has been written, educating designers on how to use generative AI during the creative process.The literature review gathers a thorough understanding of the strategic design process and the limitations and capabilities of current generative AI. With this understanding, different activities from the process are tested while using generative AI during the activities. From qualitative insights gained through reflections with respondents, insights are gathered on how the role of the strategic designer might change, how the strategic design process might change, and how to use generative AI effectively during the creative process.The study found that the strategic design process will be infused with AI-stimulated creativity, resulting in potentially more innovative outcomes. To use AI effectively, it is best to use it in a hybrid approach, using AI one-on-one and taking the results gained with AI to discuss with other stakeholders without AI. Because of the limitations of generative AI, such as bias and false information, there is an increased need for human oversight during the process.New strategic designers will be able to use generative AI as a catalyst during their workflow rather than as a way to automate the whole process. Designers should always check and iterate AI-enabled results, making them the ethical gatekeepers of the process. They are facilitators guiding other stakeholders on using generative AI to co-create with them while doing it effectively and ethically. To do so, designers' skillsets need to expand, highlighting the importance of education on using generative AI, including prompting techniques, approaches, and principles. A separate guidebook gathers insights on how to use AI effectively, serving as a guide for designers who want to use generative AI during their creative process. Strategic Product Desig
Quantifying the Influence of Salt Marshes on Wave Run-Up on a Dike During Extreme Wave Conditions: An Experimental Study
No full textSalt Marshes are a coastal ecosystem which have numerous benefits as coastal defense such as wave attenuation and can adapt to sea level rise. Wave flume tests, using a scale model of a cross-section of a salt marsh adjacent to a dike, were conducted in the Hydraulic Laboratory, to quantify the effectiveness of such a salt marsh system as flood defense (part of the Living Dikes research program). This thesis focuses on the reduction in wave run-up due to salt marshes on the adjacent dike, with a focus on high water levels. The wave run-up was measured using video processing, using a newly created algorithm to track the water movement on the dike slope. The results show a significant reduction in wave run-up due to wave attenuation over the salt marsh, further dependent on the presence of vegetation and the water depth on top of the salt marsh. The measured wave run-up values show some differences with values acquired using the TAW/EurOtop wave run-up formula. There is a correlation found with the wave steepness, where waves with a lower wave steepness do match the equation, and show a larger deviation for increasingly higher wave steepnesses.Civil Engineering | Hydraulic Engineerin
Design of a 3D scanning assist for spasticity patients in support of orthosis design
No full textThis project focuses on the exploration and development of an assistive device that allows the use of 3D scanning in the creation of personalized orthoses for spasticity patients.Spasticity is the symptom of various neurological diseases and is characterized by a prolonged contraction of the muscles. For upper limb spasticity, this leads to patients’ hands being in a cramped position and are unable to move it into a desired position without external force. To prevent the spasticity to worsen over time, orthoses are used to stabilize the hand and stretch the muscles. Currently, the hand orthoses for spasticity are still being formed the traditional way: a long process of gypsum molding, casting and the forming of thermoplastic material. Artus3D is a company that provides automated software to design and manufacture personalized hand orthoses from a single digital 3D scan of a hand. Due to the nature of spasticity, the hands need to be stretched into an open position before the 3D scanning is applicable. Together with Centrum Orthopedie, Artus3D is looking for a solution to stretch the hand and encorporate their 3D scanning & software technology into the design of spasticity orthoses. The problem consists of two parts: the orthosis design and the 3D scanning support. This project focuses on the 3D scanning support and the enabling of scanning spastic hands.The 3D scanning support keeps the spastic hand in a stable position and is designed for patient visits in the orthopaedic context. It uses a ball joint and a sliding joint in order to constrain the hand in the desired position. It is usable up to MAS 3 spasticity and has been designed to fit the 5th to 95th percentile of the population. The design follows the shape of the hand, keeps clear of important areas near the thumb, base of the hand and limits the amount of material at the lower arm. This is done with the intent of capturing as much information in the 3D scan as possible, while keeping high usability for the orthopaedic technologist and comfort for the patient. Integrated Product Desig
Accuracy of Computer-Assisted Surgery in Segmental Mandibular Resection and Reconstruction
No full textIntroduction:Virtual surgical planning is often used to prepare mandibular segment resection with subsequent reconstruction. Patient-specific cutting guides translate the planned resection and reconstruction osteotomies to the surgery. The accuracy of computer-assisted surgery is currently evaluated by heterogeneous methodologies for post-operative imaging, segmentation, registration, and accuracy measurements. Objective:This thesis aims to develop an objective, reproducible and insightful evaluation methodology. The evaluation methodology will compare planned osteotomies with actual osteotomies in segmental mandibular resection and reconstruction. The designed methodology will be applied in a retrospective study. Method:Actual osteotomies were defined by a plane fitted through manually defined points on the post-operative imaging. The actual osteotomies were aligned to the pre-operative mandible or fibula model. Distance and angular deviation were measured between the planned and actual osteotomies. Resection osteotomy distance deviation was defined as the distance between the centre of mass of the actual and planned intersection of the pre-operative mandible model and the osteotomies. The maximum distance between the intersections was also measured. Reconstruction osteotomy distance deviation was defined as the length difference between the planned and actual fibula segments. Angular deviation of the resection and reconstruction osteotomies were defined by two angular differences based on the saw slot, i.e. the angle across the saw slot (x-axis) and the angle through the saw slot (y-axis). Results:A semi-automatic novel methodology was developed. The intra-observer variation of the osteotomy localisation was ± 0.4 mm for distance deviation and ± 2.1° for the angular deviation. The inter-observer variation was ± 0.8 mm for the distance deviation and ± 2.4° for the angular deviation. Sixteen patients were included in the retrospective study. For the resection osteotomies, the absolute average distance deviation was 2.1 ± 1.9 mm for the centre of mass and 3.1 ± 2.3 mm for the maximum distance. The fibular segments differed by 2.4 ± 2.5 mm in length. Angular deviations around the x-axis were 3.7 ± 3.4° for resection and 6.9 ± 7.1° for reconstruction osteotomies, and deviations around the y-axis were 5.7 ± 5.8°and 9.1 ± 11.4°, respectively.Conclusion:The evaluation methodology provides guidelines for post-operative imaging, segmentation, osteotomy localisation, registration, and osteotomy comparison. The difference in distance deviated was within an absolute average of 3 mm. The angular deviation was significantly larger for the reconstruction osteotomies than for resection osteotomies, requiring further research.Technical Medicin
Offensive AI for Directory Enumeration
No full textWeb Vulnerability Assessment and Penetration Testing (Web VAPT) is an important cybersecurity practice that thoroughly examines web applications to uncover possible vulnerabilities. These vulnerabilities represent potential security gaps that could severely compromise the web applications' integrity and functionality if exploited by malicious entities.One of the attacks employed in the Web VAPT process is the Directory Brute-Forcing Attack. This attack aims to identify hidden directories and files not adequately secured in a web application that contain sensitive information or critical functionalities. The attack methodology involves sending many requests of possible directories or files to the target web application, where brute-force generation of requests is performed using a wordlist. Due to its brute-force nature, this attack methodology often results in enormous quantities of requests sent for a small amount of successful discoveries.With AI's quick progress and diffusion, the paradigm of Offensive AI emerges, where AI-based technologies are employed in traditional cyber attacks to make them more sophisticated and effective.This research explores whether AI can enhance the standard directory enumeration process. We propose two novel attack methodologies for performing directory brute-forcing attacks that leverage probability and Language Models (LM).Our experiments - conducted on a testbed consisting of around 1 million URLs from various domains of web applications (academic institutions, hospitals, government agencies, and business corporations) - demonstrate the superiority of our approaches over the standard brute-force attacks.In particular, the LM-based attack results in an average discoveries increase of 969%, and the probabilistic attack is more efficient at sending successful requests in the early stages of attacks in more than 94% of cases.Computer Scienc
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