Abstract: Sulfur hexafluoride (SF6), as a man-made gas, is widely used in power industry, semiconductor industry and metal-processing industry. However, SF6 is a greenhouse gas and its global warming potential is 23500 times that of CO2. Besides, SF6 is very stable, with a lifetime in the atmosphere for more than one thousand years. Under natural conditions, only the ultraviolet light can make it slowly decomposed. Thus, the emission of SF6 has a great threat to the environment. In recent years, with the development of our national economy, the use of SF6 increased dramatically. And 90% of the SF6 emissions come from the power industry. In the meantime, the emission of SF6 exists a ‘hysteresis effect’, as many of the SF6-gas insulation equipment will retire in next decades, the emission of SF6 may increase sharply, and this may put great pressure on the environment. Therefore, it’s necessary to make efforts in controlling and treating the SF6 emission. Among the SF6 abatement technologies, the non-thermal plasma(NTP) represented by the dielectric barrier discharge(DBD) can effectively degrade SF6 and is suitable for large-scale industry applications. However, its energy efficiency still gets room for improvement and this kind of method has a defect that it’s hard to regulate the degradation by-products. Therefore, this paper proposed the combination of the packed bed reactor and the DBD technology to form a packed DBD discharge system for SF6 degradation, so that to further improve the energy efficiency and regulate the selectivity of by-products. By experiment and simulation research, the following innovations have been achieved: (1) Based on the packed bed DBD platform, the power parameter and gas-phase parameters of SF6 degradation were studied. It was found that the discharge process was significantly enhanced with the addition of packing particles, and the discharge energy efficiency was improved. The increase of input voltage can obviously increase the degradation rate, but reduces the energy efficiency. The increase of SF6 initial concentration and gas flow rate can improve the energy efficiency, but reduce the degradation rate. Therefore, both degradation rate and energy efficiency should be considered in deciding basic experimental conditions. (2) Active gases, such as O2, H2O and NH3, could effectively promote the degradation rate of SF6, and changed the product selectivity. In our packed bed DBD system, O2 and H2O have the optimal concentration conditions, which are 2% and 1%, respectively. The addition of O2 can promote the generation of S-O-F products, and inhibit the selectivity of SO2, while the addition of H2O had the opposite effects. In addition, the synergistic degradation of NH3 and SF6 will produce solid products, such as NH3HF, NH4HF2 and elemental S. For gaseous products, the increase of NH3 will lead to the generation of SO2 in the final degradation products and inhibit the generation of S-O-F products. (3) Different kinds of packing materials have great impacts on the degradation system in the discharge parameters, degradation rate and energy efficiency, as well as the products distribution. In the experiment, we compared the degradation results in three systems: glass beads packing, γ-Al2O3 packing and no-packing system. The packing of glass beads effectively improved the discharge voltage amplitude and discharge power, while had a limited effect on the equivalent capacitance of the dielectric. Besides, γ-Al2O3 packing had little effect on voltage amplitude, but obviously increased the equivalent capacitance of the dielectric. Furthermore, the degradation rate and energy efficiency in γ-Al2O3 system was higher than that of glass bead system. For products selectivity, γ-Al2O3 system was more desirable, where S-O-F type of product selectivity was suppressed and the SO2 selectivity increased significantly. By contrast, the glass beads system hardly affected the product selectivity. This results are presumably due to the relatively high dielectric constant of γ-Al2O3 particles and γ-Al2O3 itself may act as a reactant or a catalyst participating in the degradation reactions. (4) The size and status of the packing particles also have significant effects on the degradation process. The systems packed with 1, 2 and 4mm γ-Al2O3 particles for SF6 degradation were compared, and the 2mm system had the best performance, which may because the 2mm system had a good balance between the active contact area and the gas residence time. In addition, the packing pellets suffered from a hydration process slightly reduced the discharge parameters in the γ-Al2O3 packing system and significantly reduced the degradation rate was, which may because the H2O molecules pre-occupied the active sites on the γ-Al2O3 surface and reduced the discharge process. (5) Based on density functional theory (DFT), the degradation process of SF6 in the packed bed DBD system was studied at atomic scale. It was found that the SF6 can occur a physical adsorption at AlⅢ active sites on γ-Al2O3 surface. The activation barrier for the first degradation step of SF6 on γ-Al2O3 surface is much lower than in gas phase, which proved that the SF6 molecule is activated on the γ-Al2O3 surface. In addition, the plasma may affect the γ-Al2O3 surface to generate excess electrons or external electric fields. This two effects can change the adsorbed SF6 molecules from physical adsorption to chemisorption, together with an obvious stretching of S-F bonds, indicating that the plasma surface effects prmote the activation and decomposition of SF6 molecules. Furthermore, the stepwise degradation process of SF6 on γ-Al2O3 surface were investigated. The influence of radicals produced by plasma on the degradation process was analyzed. It was found that via Eley–Rideal (ER) reactions, high-energy radicals could effectively reduce the activation barriers and promote the surface reactions. Finally, the degradation mechanism of SF6 molecules in the packed bed plasma system was summarized, which may provide a theoretical basis for the study of harmless degradation of SF6. Keywords: SF6; Packed Bed DBD; Discharge Parameters; Products Analysis; Degradation Mechanism

Abstract: Single cell protein (SCP), or originally named microbial protein, is the edible microbial biomass derived from e.g. microalgae, bacteria and fungi, which can be used as protein sources replacing conventional protein sources for animal feed or human food such as fishmeal and soybean (Anupama & Ravindra 2000). SCP presents great potential as protein supplement to alleviate the problem of food scarcity in the future (Nasseri et al. 2011). In general, microalgae as SCP contains above 50% protein over dry weight and specifically for the marine microalgae Dunaliella salina the amount stays around 57% (Becker 2007). Commercially the most common system for Dunaliella sp. production is the outdoor open pond, thus the microalgal cells are subjected to a natural light/dark cycle (Hosseini Tafreshi & Shariati 2009). Being photo-autotrophic microorganisms, the lack of light energy sources is a risk leading to night biomass loss (Ogbonna & Tanaka 1996). On the other hand, for some microalgae species cell division occurs primarily during the night suggesting its night protein synthesis (Cuhel et al. 1984). As a consequence, day and night metabolisms of microalgae introduced by light/dark cycles potentially will have big impacts on the biomass development, both in growth and biochemical composition. In this study, the effect of the light/dark cycle on the growth and protein synthesis of Dunaliella salina was explored in comparison with continuous light cultivation.

Abstract: Ammonia-oxidizing microorganisms (AOB and AOA) and nitrite oxidizing bacteria (NOB) are the most important organisms responsible for ammonia and nitrite oxidation in agricultural ecosystems and growing media. Ammonia and nitrite oxidation are critical steps in the soil nitrogen cycle and can be affected by the application of mineral fertilizers or organic fertilizers. The functionality of the microbial community has a major impact on the nutrient turnover and will finally influence plant performance. The microbial community associated with the growing medium and its functionality will also be influenced by the rhizosphere and the bulk soil. In our study, we used a tomato plant with a high root exudation capacity in order to stimulate microbial activity. We studied plant performance in rhizotrons (a phentotyping system for imaging roots), including an optical method (planar optodes) for non-invasive, quantitative and high-resolution imaging of pH dynamics in the rhizosphere and adjacent medium. The horticultural growing medium was supplemented with organic-derived nitrogen or ammonium derived from struvite. The possible differences in the root structure between treatments is compared with the total root length. Destructive growing medium sampling and high throughput sequencing analysis of the bacterial abundance of the communities present in the rhizosphere and the bulk soil is used to study the growing medium-associated microbial community structure and functionality, and this will be related to pH changes in the rhizosphere and the bulk soil. Our hypothesis is that the growing medium-associated microbial community structure changes depending on the nitrogen form provided and we expect a higher abundance of bacteria in the treatment with organic fertilizer and a higher abundance of AOB and NOB in the rhizosphere in comparison to the bulk soil.

Abstract: The interior and exterior Dirichlet problems for the Laplace equation in k-type Gielis domains are analytically addressed by using a suitable Fourier-like technique. A dedicated numerical procedure based on the computer-aided algebra tool Mathematica© is developed in order to validate the proposed approach. In this way, highly accurate approximations of the solution, featuring properties similar to the classical ones, are obtained. Computed results are found to be in good agreement with theoretical findings on Fourier series expansion presented by Carleson.

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.