Abstract: Superconductivity is one of the most important discoveries of the last century. With many applications in physics, engineering, and technology, superconductors are crucial to our way of living. Several material and engineering issues however prevent their widespread usage in everyday life. Comprehensive studies are being directed at these materials and their properties to come up with new technologies that will address these challenges and enhance their superconductive capabilities. In this context, numerical modeling plays an important role in the search of new solutions to existing material and engineering issues. The time-dependent Ginzburg-Landau (TDGL) theory is a powerful predictive tool for modeling the macroscopic behavior of superconductors. However most of the numerical algorithms developed so far are incapable of describing many basic properties of real superconducting devices, and are too slow on current hardware for large-scale numerical simulations necessary for their accurate description. Therefore, the purpose of this thesis is to develop high-performing numerical solutions that can correctly describe material features to be used as modeling tools of laboratory experiments. Some important innovations introduced in this work include the numerical modeling of nonrectangular geometrical shapes with complex electrical and insulating components, the inclusion of dynamic heating of the material, and the description of different types of material inhomogeneities. These encompass the principal features necessary for a complete description of the superconductive physics in real material samples. In this thesis a numerical solution is developed for modeling superconducting thin films and used to study the superconductive properties of three experimental configurations: the dynamics of vortex matter in a Corbino disk, the motion of ultrafast vortices in an hourglass-shaped microbridge, and the photon detection process in a meander-patterned nanowire. Moreover, a numerical solution is developed for modeling three-dimensional superconductors which are studied here for the first time in the type-I superconducting regime. These numerical algorithms are optimized to exploit the computational horsepower of graphics processing units (GPUs) and multicore central-processing unit (CPU) clusters such that they can achieve high-performance and be used to model large-scale problems previously impossible on conventional machines. Several computational tools are also designed to assist with the modeling of superconducting devices. These include a numerical library of the TDGL equations, a novel mechanism for the generation of complex geometries, a closed-form solver to conduct numerical simulations, and a graphics user interface (GUI) to visualize the dynamic behavior of superconductors. The contributions in this thesis ultimately push the boundaries on what is possible in state-of-the-art numerical modeling of superconductivity.

Abstract: Climate change is an ever-increasing threat to our planet, with the urbanisation of previously open spaces exacerbating the issue. The loss of open space leads to a decrease in ecosystem services, which negatively impacts the liveability in urbanised environments, and beyond. The incorporation of green infrastructure (GI) into the built environment is acknowledged as an effective and multi-functional measure to make our living environment resilient and future-proof. Notwithstanding that the local level is essential for effective GI implementation, research into local decision making is very limited. This thesis therefore aims to address two significant gaps in the implementation of GI. The first objective is to bridge the science-policy gap by integrating scientific knowledge on ES and GI into local decision-making processes. In this context, the policy dimension within this thesis involves the process of translating overarching policy objectives into practical actions within local decision-making practices, abstracting from the intricacies of higher-level policymaking itself. The second objective focuses on the people-policy gap, which involves understanding stakeholders' perspectives and priorities regarding GI and its associated ecosystem services. Through stated preference valuation techniques (discrete choice experiments and a best-worst scaling experiment), multi-stakeholder GI perceptions are gathered. Finally, a novel tool to GI valuation is developed, acknowledging the different stakeholder views and building on the insights of collaborative tool development and design. By gaining insights into the demand, prioritisation, and provision of GI from the two most important stakeholder groups at the local level (residents and local decision-makers), this research aims to foster effective communication and alignment between public preferences and policy implementation. Ultimately, addressing these gaps will contribute to more informed planning and decision-making practices related to green infrastructure. The overall goal of this thesis is to enhance the uptake of GI knowledge in the local decision-making context, proposing pathways to facilitate and optimise investments in public GI.

Abstract: Atomic Spectroscopy Optical (atomic absorption spectroscopy, AAS; atomic emission spectroscopy, AES; atomic fluorescence spectroscopy, AFS; and optogalvanic spectroscopy) and mass spectrometric (magnetic sector, quadrupole mass analyzer, QMA; quadrupole ion trap, QIT; Fourier transform ion cyclotron resonance, FTICR; and time-of-flight, TOF) instrumentation are well suited for coupling to the glow discharge (GD). The GD is a relatively simple device. A potential gradient (500–1500 V) is applied between an anode and a cathode. In most cases, the sample is also the cathode. A noble gas (mostly Ar) is introduced into the discharge region before power initiation. When a potential is applied, electrons are accelerated toward the anode. As these electrons accelerate, they collide with gas atoms. A fraction of these collisions are of sufficient energy to remove an electron from a support gas atom, forming an ion. These ions are, in turn, accelerated toward the cathode. These ions impinge on the surface of the cathode, sputtering sample atoms from the surface. Sputtered atoms that do not redeposit on the surface diffuse into the excitation/ionization regions of the plasma where they can undergo excitation and/or ionization via a number of collisional processes, and the photons or ions created in this way can be detected with optical emission spectroscopy or mass spectrometry. GD sources offer a number of distinct advantages that make them well suited for specific types of analyses. These sources afford direct analysis of solid samples, thus minimizing the sample preparation required for analysis. The nature of the plasma also provides mutually exclusive atomization and excitation processes that help to minimize the matrix effects that plague so many other elemental techniques. In recent years, there is also increasing interest for using GD sources for liquid and gas analyses. In this article, first, the principles of operation of the GD plasma are reviewed, with an emphasis on how those principles relate to optical spectroscopy and mass spectrometry. Basic applications of the GD techniques are considered next. These include bulk analysis, surface analysis, and the analysis of solution and gaseous samples. The requirements necessary to obtain optical information are addressed following the analytical applications. This article focuses on the instrumentation needed to make optical measurements using the GD as an atomization/excitation source. Finally, mass spectrometric instrumentation and interfaces are addressed as they pertain to the use of a GD plasma as an ion source. GD sources provide analytically useful gas-phase species from solid samples. These sources can be interfaced with a variety of spectroscopic and spectrometric instruments for both quantitative and qualitative analyses.