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: Moore’s Law has driven the electronics industry for the past half century. However, the doubling of transistors about every two years is beginning to break down, owing to fundamental limits that arise as they approach the atomic length. As a result, the search for new pathways for electronics has become crucial. Among potential candidates, the discovery of magnetic textures known as skyrmions has attracted considerable interest and attention in spintronic technology, which relies on both the electron charge and its spin. The unusual topological and particle-like behavior launched skyrmions into the spotlight of scientific research. Topological protected stability, nanoscale size, and low driving currents needed to move them make skyrmions promising candidates for future consumer nanoelectronics. Recent advances in the field have provided all of the basic functions needed for carrying and processing information. In this thesis, we procure to advance the current understanding of skyrmion physics, and explore their potential to replace conventional electronics technology. First, the fundamental properties and lifetimes of racetrack skyrmions at room temperature are investigated. We discover that skyrmions can easily collapse at the boundary in laterally finite systems, and propose ways to improve their stability for constrained geometries. Then, pinning of single skyrmions on atomic defects of distinct origins are studied. We reveal that the preferred pinning positions depend on the skyrmion size and type of defect being considered, and discuss applications where control of skyrmions by defects is of particular interest. Next, we explore other magnetic configurations that can compete with skyrmions when considering new materials, and describe a previously unseen mechanism for collapse of skyrmions into cycloidal spin backgrounds. Finally, switching and interactions between skyrmions with distinct topologies are reported. We find that skyrmions transition to higher or lower topologies by absorbing a unit spin texture. The interactions between skyrmions of different topological charges can be attractive or repulsive, leading to the formation of arranged clusters. We conclude with a numerical library for simulating magnetic skyrmions in various scenarios.

Abstract: uIn this work, we discuss three novel Ti (germano-)silicidation techniques featuring respectively the pre-contact amorphization implantation (PCAI), the TiSi co-deposition, and Ti atomic layer deposition (ALD). All three techniques form TiSix(Ge-y) contacts with ultralow contact resistivity (rho(c)) of (1-3)x10(-9) Omega.cm(2) on both highly doped n-Si and p-SiGe substrates: these techniques meet rho(c) requirement of 5-14 nm CMOS technology and feature unified CMOS contact solutions. We further discuss the compatibility of these techniques to the realistic CMOS transistor fabrication.

Abstract: We investigate at the atomic level the most probable phase transformations under strain, that are responsible for the ferroelectric/ antiferroelectric behavior in Hf1-xZrxO2 materials. Four different crystalline phase transformations exhibit a polar/non-polar transition: monoclinic-to-orthorhombic requires a gliding strain tensor, orthorhombic-to-orthorhombic transformation does not need strain to polarize the material, whereas tetragonal-to-cubic cell compression and tetragonal-to-orthorhombic cell elongation destabilizes the non-polar tetragonal phase, facilitating the transition towards a polar atomic configuration, therefore changing the polarization-electric field loop from antiferroelectric to ferroelectric. Oxygen vacancies can reduce drastically the polarization reversal barriers.

Abstract: Synthetic micro‐ and nanomotors (MNMs) are tiny objects that can autonomously move under the influence of an appropriate source of energy, such as a chemical fuel, magnetic field, ultrasound, or light. Chemically driven MNMs are composed of or contain certain reactive material(s) that convert chemical energy of a fuel into kinetic energy (motion) of the particles. Several different materials have been explored over the last decade for the preparation of a wide variety of MNMs. Here, the discovery of materials and approaches to enhance the efficiency of chemically driven MNMs are reviewed. Several prominent applications of the MNMs, especially in the fields of biomedicine and environmental science, are also discussed, as well as the limitations of existing materials and future research directions.

Abstract: In this study, the impact of diclofenac (DCF), an antiinflammatory drug being extensively used in human health care and veterinary treatment, on the production of volatile fatty acids (VFAs) from anaerobic fermentation of waste activated sludge (WAS) was investigated for the first time. Experimental results showed that when DCF concentration increased from 2.5 to 25 mg/kg total suspended solid (TSS), the maximum production of VFAs increased from 599 to 1113 mg COD/L, but further increase of DCF to 47.5 mg/kg TSS decreased VFAs yield to 896 mg COD/L. The mechanism investigation revealed that DCF had no effect on the hydrolysis process, promoted the process of acidogenesis, acetogenesis, and homoacetogenesis, but severely inhibited methanogenesis, leading to the accumulation of VFAs. Microbial community analysis showed that the addition of DCF could promote the relative abundance of VFAs (especially acetic acid) producers, which was well consistent with the results obtained above.

Abstract: Autotrophic denitrification with sulfur is an underexplored alternative to heterotrophic denitrification to remove nitrate from wastewater poor in organics. The application on ion exchange regeneration water (19.432.1 mS cm−1) is novel. Three fixed bed reactors were tested at 15 °C for >4 months, inoculated with activated sludge from sewage treatment. All were fast in start-up (<10 days) with high performance (94 ± 2% removal efficiency). pH control with NaOH rendered higher nitrate removal rates than limestone addition to the bed (211 ± 13 vs. 102 ± 13 mg N L−1 d−1), related to higher pH (6.64 vs. 6.24) and sulfur surface area. Bacterial communities were strongly enriched in Sulfurimonas (6367%) and Thiobacillus (2426%). In an economic comparison, sulfur-based denitrification (5.3 kg−1 N) was 15% cheaper than methanol-based denitrification (6.22 kg−1 N) and both treatments were opex dominated (85.9 vs. 86.5%). Overall, the technological and economic feasibility should boost further implementation of sulfurotrophic denitrification.

Abstract: Hydrogenotrophic denitrification is a novel and sustainable process for nitrogen removal, which utilizes hydrogen as electron donor, and carbon dioxide as carbon source. Recent studies have shown that nitrous oxide (N2O), a highly undesirable intermediate and potent greenhouse gas, can accumulate during this process. In this work, a new mathematical model is developed to describe nitrogen oxides dynamics, especially N2O, during hydrogenotrophic denitrification for the first time. The model describes electron competition among the four steps of hydrogenotrophic denitrification through decoupling hydrogen oxidation and nitrogen reduction processes using electron carriers, in contrast to the existing models that couple these two processes and also do not consider N2O accumulation. The developed model satisfactorily describes experimental data on nitrogen oxides dynamics obtained from two independent hydrogenotrophic denitrifying cultures under various hydrogen and nitrogen oxides supplying conditions, suggesting the validity and applicability of the model. The results indicated that N2O accumulation would not be intensified under hydrogen limiting conditions, due to the higher electron competition capacity of N2O reduction in comparison to nitrate and nitrite reduction during hydrogenotrophic denitrification. The model is expected to enhance our understanding of the process during hydrogenotrophic denitrification and the ability to predict N2O accumulation.