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Exploring Bio-Based Plasticizers for Technical Rubber Goods
No full textThe rubber industry is using phthalates as plasticisers in technical rubber goods due to their excellent compatibility, low volatility, and cost-effectiveness. However, growing concerns about their adverse impact on health and the environment have driven the search for sustainable alternatives. One promising approach is the use of bio-based plasticisers due to their renewable nature, non-toxicity, and biodegradability. This study explores the feasibility of replacing a conventional diisononyl phthalate (DINP) with bio-based plasticizers in nitrile butadiene rubber (NBR) compounds. The new bio-based plasticizer achieves equivalent processing and mechanical performance by using only half of the amount (in phr) which is required for the traditional petroleum-based plasticizer. This research supports the development of sustainable rubber materials and contributes to reducing the dependence on fossil-based materials while maintaining high-quality standards
Privacy-Utility Trade-Off in Healthcare Metadata Sharing and Beyond:A Normative and Empirical Evaluation at Inter and Intra Organizational Levels
Get PDFIn the contemporary world, big data analytics facilitate better-informed, efficient, and effective decision-making across various domains. In healthcare, the privacy-utility trade-off (PUT) emerges as a central challenge. This trade-off reflects the tension between the utility derived from the precision of data analytics and the privacy risks posed to individuals, organizations, and communities at local, national, and international levels. Using healthcare data effectively while maintaining privacy and regulatory compliance remains a significant practical and technical challenge. To empirically evaluate the end-to-end processes in healthcare metadata sharing and beyond, process mining (PM) served as a suitable mean for a bottom up, data driven identification of the deviations in ‘as is’ and ‘should be’ states in metadata sharing. Moreover, to normatively evaluate the healthcare metadata sharing landscape, and to establish theoretical foundations as a top-down approach, the content analysis of scientific literature, regulatory frameworks, and official sources served the required purpose. The findings are represented through conceptual models (REA ontology, e3 value modeling, and BPMN 2.0) and evaluated by domain experts to ensure structural veracity and practical applicability. After the exploration of the healthcare metadata sharing landscape, the thesis provides evidence based, solution measures to ascertain process utility and privacy preservation of data subjects by designing, and evaluating the privacy enhancing process mining, project methodology (PEPM2), the assessment matrix for PEPM2, the core components for process utility in process mining, and the process utility evaluation matrix (PUEM). Evaluations using expert opinion and real-world case studies demonstrate tangible improvements in process optimization, privacy compliance, and data utility. For example, the application of PEPM2 allowed the identification of bottlenecks in data sharing workflows and provided actionable recommendations to improve workflow efficiency by enhancing privacy preservation. Despite these contributions, certain limitations must be acknowledged. The evaluation relies on a limited number of expert reviews and case studies, which can constrain generalizability. Furthermore, the rapidly evolving nature of data technologies and privacy regulations poses challenges for long-term applicability. Future research should extend empirical validation across domains and explore dynamic adaptations of the proposed methodologies, evaluation frameworks, and conceptual models to adapt to the ever-changing data-driven, technological, and regulatory landscapes
Vapour-driven solutal Marangoni flow transition across the vapour-liquid equilibrium at the droplet contact line
Get PDFVapour-driven solutal Marangoni effects have been studied extensively due to their potential applications, including mixing, coating, and droplet transport. Recently, the absorption of highly volatile organic liquid molecules into water droplets, which drives Marangoni effects, has gained significant attention due to its intricate and dynamic physical behaviours. To date, steady-state scenarios have been considered mainly by assuming the rapid establishment of vapour-liquid equilibrium. However, recent studies show that the Marangoni flow arises even under uniform vapour concentration, and requires a considerable time to develop fully. It indicates that the vapour-liquid equilibrium takes longer to establish than was previously assumed, despite earlier studies reporting that vapour molecules instantly adsorb on the interface, highlighting the importance of observing transient flow patterns. Here, we experimentally and numerically investigate time-dependent flow structures throughout the entire lifetime of a droplet in ethanol vapour environments. Under two distinct vapour boundary conditions of uniform and localised vapour distributions, a significant flow structure change consistently occurs within the droplet. The time-varying ethanol vapour mass flux from numerical simulation reveals that the flow transition is caused by the high vapour absorption flux at the droplet contact line, due to the geometric singularity there. Based on the detailed analysis of the surface tension gradient along the droplet interface, we identify that the flow transition occurs before and after the vapour-liquid equilibrium is achieved at the droplet contact line, which induces the flow direction change near the contact line.</p
Performance comparison of streptavidin magnetic beads for epcam expressing cancer cell lines for circulating tumor cell (CTC) enrichment in a flow-through immunomagnetic system
Get PDFCirculating tumor cells (CTCs) are important biomarkers for cancer diagnosis and treatment monitoring. However, their scarcity limits their utility as current enrichment techniques are hampered by low volume throughput and/or the inability to capture CTCs with low target antigen densities. Our group previously reported a device capable of processing samples in a flow manner using an optimized Halbach array to enhance the capture of low EpCAM-expressing cells (Flow-through Immunomagnetic CTC Enrichment system). In this study, we tested the capture efficiency of eight commercially available streptavidin magnetic beads using this device to identify the most suitable bead. Results indicate that using this system, the best-performing magnetic beads are in the~100 to~150nm size range. Considering the combination of binding efficiency and final sample purity, we found that among the beads tested in combination with biotinylated anti-EpCAM, MojoSort Streptavidin Nanobeads performed the best, with high capture efficiencies for both the high EpCAM expressing LNCaP and low EpCAM expressing PC3–9 cell lines. For CTC enrichment from the blood of cancer patients, reducing the number of WBCs co-enriched with these beads will be essential, especially when processing large-volume samples acquired, for instance, through diagnostic leukapheresis to overcome the limitations caused by the scarcity of CTCs.</p
Develop a Versatile ECM Framework Capable of Accurately Representing Multiple Cell Types
No full textBattery electric equivalent circuit model (ECM) parameters are widely popular for performing modelling and estimation of energy storage systems across various applications, such as grid storage and electric vehicle applications. The modelling parameters and estimated values (State of Charge (SoC) and State of Health (SoH)) form the basis of different analyses performed on the batteries. One of the critical challenges is to develop an ECM that is versatile enough to capture the varied nature of battery cell types because of changes in chemistry, geometry, applications, and operating conditions. In this paper, a versatile equivalent circuit model (ECM) development framework is approached, which is capable of precisely representing various cell types. Statistical analysis is performed to identify the most dominating factor among the ECM parameters, which affects most changes in cell manufacturing and chemistry, directing towards developing a universal equivalent circuit modelling approach
Odd-even effects in lead-iodide-based Ruddlesden-Popper 2D perovskites
Get PDFTwo-dimensional (2D) halide perovskites are a versatile material class, exhibiting a layered crystal structure, consisting of inorganic metal-halide sheets separated by organic spacer cations. Unlike their 3D counterparts, 2D perovskites have less strict geometric requirements, allowing for a wider range of molecules to be incorporated. This potentially offers a way to engineer the properties of a 2D perovskite through adequate selection of the organic spacer cations. Our study systematically analyzes the effect of spacer cation length on the electronic and optical properties of Ruddlesden-Popper lead-iodide-based 2D perovskites, using alkylammonium cations of varying chain lengths. Intriguingly, no linear correlation between interlayer distance and the optical gap or valence band position is observed in our measurements. Rather it matters whether the spacer cation contains an odd or even number of carbon atoms in the chain. Notably, these odd-even effects manifest in variations of ionization energy, optical gap as well as charge carrier mobility. Density functional theory calculations reproduce the changes in optical properties, allowing us to identify the underlying mechanism: while even-numbered carbon chains pack efficiently within the organic spacer layer, the shorter odd-numbered chains increase distortions. These distortions lead to variations in the Pb-I-Pb bond angle within the inorganic sheets, resulting in the observed odd-even effect in the (opto-)electronic properties. This understanding will be helpful to make more informed choices regarding the incorporated spacer molecules which can potentially help to enhance performance when integrating such 2D perovskite interlayers into devices.</p
Making a difference: describing and evaluating the impact of the Dutch CardioVascular Alliance
Get PDFIntroduction: In 2018, the Dutch CardioVascular Alliance (DCVA), a collaboration between 24 partners in the cardiovascular field, expressed the ambition to reduce the cardiovascular disease (CVD) burden in the Netherlands by 25% in 2030. This project aimed to evaluate the extent to which the activities within the DCVA contribute to a reduction in the burden defined as morbidity and mortality combined. Methods: The role and potential impact of the DCVA was assessed. Three assessments were conducted: 1) to determine the potential impact of consortia (n = 32) using a checklist; 2) to estimate the potential health benefit (quality-adjusted life years, (QALYs)) and cost savings from a snapshot of consortia (n = 4). Results: Most of the consortia focused on treatment (31%), followed by secondary prevention/monitoring (23%) and diagnosis (23%). Almost all consortia (n = 31) aim to reduce morbidity and two-thirds (n = 21) aim to reduce mortality. The four consortia evaluated were Check@Home, LoDoCo2, CONTRAST 2.0 and IMPRESS, with pathways in screening, treatment, treatment and diagnosis, respectively. The total estimated cumulative QALYs gained (from 2023 to 2030) were 1,694, 362, 2,783, and 3,655 respectively. Discussion: Although it is impossible to estimate the full impact of the DCVA itself, the presented checklist and analyses may increase awareness of the different DCVA activities, roles, and consortia. Existing HTA methods can support the exploration of the potential impact generated by each consortium within the DCVA. The current portfolio of DCVA consortia contributes extensively to the DCVA goal of reducing the CVD burden, provided there is effective support for the adoption and implementation of innovations.</p
Single photons in linear optics:Quantum computing and quantum simulations
Get PDFThis dissertation explores the use of single photons in integrated photonic circuits as a platform for quantum computation and quantum simulation. In the noisy intermediate-scale quantum (NISQ) era, photonic implementations of boson sampling provide one of the most promising routes to demonstrating quantum advantage, while also enabling insight-driven experiments that probe many-body interference and computational complexity.The first part of the thesis is devoted to the hardware development and characterization of programmable silicon nitride photonic processors. We demonstrate large-scale multi-photon interference in a 20-mode universal processor, establishing the potential of integrated photonics for scaling up boson sampling experiments. In parallel, we introduce a validation protocol based on detector binning, implemented on a 12-mode predecessor of the device. Together, these studies advance the photonic platform itself, focusing on scalability, versatility, and benchmarking, rather than direct applications.The second part turns to quantum simulation. We first present a photonic simulation of a spin-foam amplitude from loop quantum gravity, illustrating how multi-photon interference can provide a testbed for problems in fundamental physics. We then implement a particle-number-difference Maxwell demon using conditional operations on photon subsets in a multi-mode interferometer. This experiment probes the link between thermodynamics and information theory, showing how a photonic platform with single-photon resolution and quantum interference can be used to explore information-driven control of physical systems.The final part addresses quantum computation, where we demonstrate a boson-sampling-accelerated Monte Carlo integrator. This hybrid quantum–classical algorithm represents one of the few proposals to extend boson sampling toward practical applications while plausibly retaining its computational hardness. We validate the method in a proof-of-principle experiment reproducing perturbative corrections in a model inspired by Efimov physics.Altogether, the results presented in this thesis position integrated photonics as both a scalable hardware platform for multi-photon experiments and a versatile tool for advancing quantum simulation and computation
Nature-based solutions for reducing flood risk:A case study in South Tongu District, Ghana
No full textFlooding poses a significant threat to socio-economic and ecological systems in Ghana, particularly in rural districts such as South Tongu. Conventional flood management strategies have proved inadequate in addressing recurrent and severe flooding in the region. This study investigates the effectiveness and practicality of implementing Nature-based Solutions (NbS) for flood risk management in South Tongu District, Ghana. Using a mixed-methods approach, the research integrates spatial analysis, hydrological modelling via the fast flood model, and expert interviews to assess flood-prone areas, evaluate selected NbS interventions, and examine implementation feasibility.Three NbS, permeable surfaces, river restoration, and riparian/forested buffers, were selected based on literature review and local applicability. The fast flood model was used to simulate baseline and intervention scenarios. Results indicate that all three measures reduced flood extent, depth and affected buildings, with river restoration showing the most significant reduction. Permeable surfaces were most effective in built-up areas, while riparian buffers contributed to reduced runoff and erosion along riverbanks.Expert interviews revealed key practical challenges, including high initial costs, limited stakeholder awareness, and weak institutional coordination. Nonetheless, local soil conditions and vegetation support the feasibility of NbS integration, provided site-specific adaptations are made. The study concludes that NbS offer a viable and sustainable alternative to traditional flood management approaches in rural Ghana. By aligning ecological restoration with risk reduction, these interventions support the achievement of SDGs related to climate resilience, sustainable cities, and land use. Recommendations are made for policy integration and scaling up NbS across similar vulnerable regions
