In this dissertation, light management techniques with front textures for thin-film silicon superstrate configuration solar cells are presented. Specifically, the textures are developed on glass to act as light scatterers at interfaces in thin-film devices. The thesis aims to study textures made on glass with a broader idea of transferring it to aluminium folie for fabricating pre-textured transparent conductive oxide (TCO)s in the roll-to-roll fabrication by LiFT PV B.V.

This thesis aims to answer a main question:
How to engineer a front glass texture with which high-performing thin-film silicon superstrate solar cells can be fabricated?

This main question is addressed through four different key questions in five different chapters. The optimisation of thin-film silicon deposition conditions is presented in Chapter 2. Amorphous silicon and nanocrystalline silicon layers are deposited at very high frequency conditions to obtain device-grade photoactive silicon. The processing conditions optimised in this chapter are used to fabricate silicon absorber layers in subsequent Chapters 3, 4, and 5 of the thesis to study light trapping by glass textures.

In Chapter 3, the glass surface is textured with randomly scattered texturing shapes (craters or protrusions), without an explicit placement rule. The textures are referred to as “random textures”. This chapter addresses the sub-question:
How does light interact with glass textures featuring nano-scale structures superimposed on micro-scale textures, and how does the resulting morphology influence nano-crystalline silicon growth?

This chapter demonstrates that a sequential wet etching technique can superimpose nano-sized craters on micro-sized craters on glass, with a higher optical performance and efficiency in solar cells when compared to both micro- and nano-textures individually.

Textures characterised by a repeating pattern of shapes at fixed, regular intervals are considered “periodic textures”. Chapter 4 specifically addresses the question:
How to design a periodic glass texture composed of micro-scale hexagonal craters to maximise light scattering efficiency?

To answer this, photolithography is used as a technique to make hexagonal-shaped micrometre-scale craters on the glass surface. The hexagonal textures increased the light scattering capability with deeper craters and higher periodicity value. Glass with hexagonal micro-textures demonstrated a diffusivity as high as 50% in the near infrared light.

Once the design of periodic textures is completed, the recipe to generate hexagonal shapes with different feature sizes is known. Chapter 5 answers the question:
How does a hexagonal periodic texture on glass influence light interaction, and how do its morphological characteristics affect the performance of thin-film silicon superstrate solar cells?

The hexagonal periodic textures made on glass are studied in detail for their light scattering and diffraction effects. Additionally, nanocrystalline silicon single-junction solar cells are fabricated on these textures with different feature sizes and studied for their electrical and optical performance. An optical performance of 28.60 mA/cm² was achieved for the single junction nc-Si:H solar cells without any external antireflective measures, indicating a high potential for hexagonal textures on glass in multijunction thin-film solar cell applications.

Chapter 6 explores light scattering of the developed textures when implemented on multijunction solar cells. The challenge of Fabry-Pérot interference in multilayers with contrasting refractive indices is identified in multijunctions, limiting their optical performance. This study addresses the sub-question:
What impact do interface and bulk scattering have on the optical performance of multijunction cells, and which strategies can effectively mitigate interference effects caused by optical micro-cavities?

For this, light scattering in bulk TCO grains, combined with random and periodic textures, is studied in detail. Hexagonal craters on glass, combined with a 0.9 micrometre thick i-ZnO layer, effectively mitigated fringes formed by all optical cavities in the device.

The design principles discussed in this work are not restricted to amorphous silicon/nanocrystalline silicon tandem devices but can be extended to any thin-film multijunction solar cell that constitutes layers with contrasting refractive indices.

Agriculture accounts for roughly 72% of global freshwater withdrawals, but irrigation is often still based on intuition or fixed schedules. Model-based and data-driven approaches have shown promise, but they mostly rely on historical datasets or crop-specific knowledge that are unavailable in many settings. This thesis addresses that gap by proposing an irrigation control framework that requires no prior data and can learn the system dynamics online during the growing season. The framework combines three components: a Zone Model Predictive Control strategy, an online model estimator based on Recursive Least Squares (RLS), and a Readily Available Water (RAW) estimator. The framework is evaluated using the AquaCrop simulator on a sugarcane case study in southern Mozambique. Results show that the proposed framework performs comparably to a static controller preconfigured with historical data and crop-specific knowledge, while requiring neither. A sparse measurement strategy is also evaluated, reducing the number of required soil moisture measurements by around 65% with little impact on performance. That said, learning the system online comes with trade-offs, and the framework does not consistently outperform a well-configured static model. Together, the results suggest that effective predictive irrigation control is achievable in data-scarce environments.

Offshore wind expansion in the North Sea is putting pressure on maritime safety, as increasing fixed infrastructure reduces manoeuvring space and increases collision and disruption risk. This thesis examines how shipping safety is integrated into offshore wind planning as the sector scales up. It compares governance arrangements in the Netherlands and the United Kingdom, two mature offshore wind contexts with similar geography but different institutional designs.

The central research question asks how vertical coordination, horizontal coordination, Safety-I/Safety-II approaches, and compliance design shape the integration of shipping safety into offshore wind planning in both countries as offshore wind scales up. The study applies a comparative case design combining document analysis and expert interviews, structured around four analytical dimensions: vertical allocation of responsibilities, horizontal cross-sector coordination, safety mode (Safety-I versus Safety-II), and dual-layer compliance architecture.

Both countries channel navigational safety through a multi-stage governance funnel, but differ in where safety alignment is stabilised. The Netherlands employs upstream stabilisation through plan-led steering: safety principles and spatial assumptions are embedded early via marine spatial planning and state-led site preparation, pushing consequential trade-offs to pre-tendering stages. The United Kingdom relies on downstream stabilisation through developer-led proof in consenting: early screening processes exist, but most safety issues are resolved through Navigational Risk Assessments and evidence during the consenting phase, preserving flexibility while increasing vulnerability to late lock-in and costly redesign.

Several findings emerge. Decision power does not eliminate the need for evidence, but it changes how evidence must be produced and justified. Safety-I continues to provide the non-negotiable prescriptive baseline, while Safety-II is growing in importance as sea space becomes denser and cumulative risks harder to anticipate through incident-based learning alone. Scenario modelling, near-miss learning, and structured learning loops are becoming essential evidence-production tools. Both systems depend on a dual-layer compliance structure combining prescriptive baselines with performance-based proof, but this functions robustly only when review capacity, consistent methods, and shared data baselines are in place.

Based on these findings, the thesis identifies four practical priorities for strengthening navigational safety governance as offshore wind scales. Institutionalising anticipatory evidence production through routine scenario-based reviews and near-miss learning. Strengthening upstream screening before commercial and procedural lock-in occurs. Investing in review capacity and consistency so regulators can evaluate deviations from prescriptive baselines transparently. Building a shared evidence base of traffic patterns, manoeuvring needs, and port practice projections to enable cumulative impact assessment across projects and institutions.

Osteoarthritis (OA) is a joint disease that causes cartilage degeneration, stiffness, and unpredictable, painful flare-ups. Current diagnostic methods provide only clinical snapshots. This leaves a lack of continuous insight into symptom changes in daily life. This project was driven by the hypothesis that elevated localised skin temperature and more frequent or intense acoustic joint emissions (crepitus) could indicate a flare-up and increased pain. To test this, a non-invasive smart wearable needed to be developed. By continuously measuring thermal and acoustic signals in daily life, this smart knee-wearable aims to objectively detect flare-ups and, in the future, bridge the gap between subjective pain and objective clinical data.

To achieve this goal, the Double Diamond design methodology was applied. After a discovery phase of literature research and expert interviews, a Programme of Requirements was established in the define phase. An iterative design process was followed for the development phase. Ideas were explored in Virtual Reality, and physical prototypes were made. These iterations were tested for technological feasibility and comfort, with input from both healthy individuals and OA patients.

The resulting prototype is a comfortable, breathable knee sleeve made of a spandex-like material and called Lola, meaning Long-term osteoarthritis logging assistant. The design has an open kneecap and knee hollow for optimal freedom of movement. With silicone anti-slip elastic to keep it in place. Integrated technology includes a XIAO ESP32-S3 microcontroller, SD card module, MEMS microphone, and several NTC temperature sensors. Conductive yarn, stitched in a zigzag stitch, enables seamless, flexible integration of components.

The validation showed that the wearable effectively records the desired data. During controlled movements, the acoustic algorithm distinguished a healthy knee from an OA knee, but continuous walking and friction from long trousers caused mechanical noise in the sound data. The temperature sensors also accurately recorded physiological heat changes. Furthermore, the wearable scored highly for comfort. Test subjects reported forgetting they wore it within 30 minutes. However, patients also reported that a wraparound model would be easier to put on and is an area for improvement.

In conclusion, developing a non-invasive wearable to measure crepitus and temperature for patients with OA is feasible. Although it is not a market-ready medical product, and noise-reduction software still needs refinement, this proof-of-concept shows that continuous, objective monitoring of osteoarthritis in daily practice is possible and valuable, provided that several aspects of the wearable are further investigated and optimised.

his thesis investigates the modelling of a ship’s magnetic field, by means of an equivalent source model defined on an arbitrarily shaped surface enclosing the source. This setup allows for the use of measurements close to the enclosing surface, such as on the seabed in shallow waters. A multipolar basis is introduced to reduce the dimensionality of the problem, which allows for a convenient mapping to the Decreasing Spherical Harmonic Expansion to describe the far field with low computational costs. It is found that the method performs well in determining a source model and predicting the magnetic field in new locations, provided that enough well-distributed measurements are available. The method remains accurate in the presence of noise, although measurements very close to the enclosing surface reduce performance, a reduction attributed to an approximation that may be improved. Bayesian inference is used to stabilise the method when a low number, badly distributed and/or noisy measurements are available. We find that this regularisation indeed enables the use of the method in such situations. In addition, it is investigated whether orthogonality of the basis is required. It is found that it is not, and that a non-orthogonal basis can yield slightly better results. This suggests that the discretisation of the surface and the choice of solution space of the equivalent source are the main limiting factors in improving the solutions.