Abstract: The construction of uniform nanostructure with larger surface area electrodes is a huge challenge for the highvalue added energy storage application. Herein, we demonstrates ZIF67@ZIF8 (core-shell) and ZIF8@ZIF67 (reverse core-shell) nanostructures using a low-cost wet chemical route and used them as supercapacitors. Pristine ZIF-67 and ZIF-8 was used as reference electrodes. Benefiting from the synergistic effect between the ZIF8 and ZIF67, the ZIF8@ZIF67 exhibited the outstanding electrochemical consequences owing to its larger surface area with uniform hexagonal morphology. As optimized ZIF8@ZIF67 nanostructure displayed the highcapacity of 1521 F/g at 1 A/g of current density in a three-electrode assembly in 1 M KOH electrolyte compared with other as-fabricated electrodes. In addition, the ZIF8@ZIF67 nanostructure employed into the symmetric supercapacitors (SSCs) with 1 M KOH electrolyte in two-electrode setup and it exhibited still superior output including capacity (249.8 F/g at 1 A/g), remarkable repeatability (87 % over 10,000 GCD cycles) along with high energy and power density (61.2 Wh/kg & 1260 W/kg). The present study uncovers the relationship between the larger surface area and electrocatalyst performance, supporting an effective approach to prepare favorable materials for enhanced capacity, extended lifespan, and energy density.

Abstract: We calculate bubble nucleation rates in a Lennard-Jones fluid through explicit molecular dynamics simulations. Our approach-based on a recent free energy method (dubbed reweighted Jarzynski sampling), transition state theory, and a simple recrossing correction-allows us to probe a fairly wide range of rates in several superheated and cavitation regimes in a consistent manner. Rate predictions from this approach bridge disparate independent literature studies on the same model system. As such, we find that rate predictions based on classical nucleation theory, direct brute force molecular dynamics simulations, and seeding are consistent with our approach and one another. Published rates derived from forward flux sampling simulations are, however, found to be outliers. This study serves two purposes: First, we validate the reliability of common modeling techniques and extrapolation approaches on a paradigmatic problem in materials science and chemical physics. Second, we further test our highly generic recipe for rate calculations, and establish its applicability to nucleation processes.

Abstract: Estimating personal exposure to air pollution is a crucial component in identifying high-risk populations and situations. It will enable policy makers to determine efficient control strategies. Cycling is again becoming a favorite mode of transport both in developing and in developed countries due to increasing traffic congestion and environmental concerns. in Europe, it is also seen as a healthy sports activity. However, due to high levels of hazardous pollutants in the present day road microenvironment the cyclist might be at a higher health risk due to higher breathing rate and proximity to the vehicular exhaust. In this paper we present estimates of the exposure of a cyclist to particles of various size fractions including ultrafine particles (UFP) in the town of Mol (Flanders, Belgium). The results indicate relatively higher UFP concentration exposure during morning office hours and moderate UFP levels during afternoon. The major sources of UFP and PM(10) were identified, which are vehicular emission and construction activities, respectively. We also present a dust mapping technique which can be a useful tool for town planners and local policy makers. (C) 2008 Elsevier B.V. All rights reserved.

Abstract: The number of agricultural cooperatives increased quickly in Ethiopia since the 1990s. While many papers studied the impact of membership of Ethiopian cooperatives, not much is known on their performance. This study takes a cooperative-level perspective which is unique in an African context. It compares the economic performance proxied by sales revenue and profit of a wide range of agricultural cooperatives in northern Ethiopia. Data were collected from 511 agricultural cooperatives in 12 districts of Tigray. The contributing factors of the performance are analyzed with Ordinary Least Squares regression (OLS) and Heckman selection models. Our results underscore the importance of membership size, total assets, presence of conflict among members, and union membership. Chairperson characteristics and the internal organization of a cooperative seem to be less correlated to performance.

Abstract: Purple non-sulphur bacteria (PNSB) are an emerging group of microbes attractive for applied microbiology applications such as wastewater treatment, plant biostimulants, microbial protein, polyhydroxyalkanoates and H-2 production. These photoorganoheterotrophic microbes have the unique ability to grow selectively on organic carbon in anaerobic photobioreactors. This so-called selectivity implies that the microbial community will have a low diversity and a high abundance of a particular PNSB species. Recently, it has been shown that certain PNSB strains can produce antimicrobials, yet it remains unclear whether these contribute to competitive inhibition. This research aimed to understand which type of antimicrobial PNSB produce and identify whether these compounds contribute to their selective growth. Mining 166 publicly-available PNSB genomes using the computational tool BAGEL showed that 59% contained antimicrobial encoding regions, more specifically biosynthetic clusters of bacteriocins and non-ribosomal peptide synthetases. Inter- and intra-species inhibition was observed in agar spot assays for Rhodobacter blasticus EBR2 and Rhodopseudomonas palustris EBE1 with inhibition zones of, respectively, 5.1 and 1.5-5.7 mm. Peptidomic analysis detected a peptide fragment in the supernatant (SVLQLLR) that had a 100% percentage identity match with a known non-ribosomal peptide synthetase with antimicrobial activity.

Abstract: The added value of supervised Machine Learning (ML) methods to determine the Absolute Configuration (AC) of compounds from their Vibrational Circular Dichroism (VCD) spectra was explored. Among all ML methods considered, Random Forest (RF) and Feedforward Neural Network (FNN) yield the best performance for identification of the AC. At its best, FNN allows near-perfect AC determination, with accuracy of prediction up to 0.995, while RF combines good predictive accuracy (up to 0.940) with the ability to identify the spectral areas important for the identification of the AC. No loss in performance of either model is observed as long as the spectral sampling interval used does not exceed the spectral bandwidth. Increasing the sampling interval proves to be the best method to lower the dimensionality of the input data, thereby decreasing the computational cost associated with the training of the models.

Abstract: This study examines five benzyl alcohol derivatives and three chemically similar compounds and compares them against benzyl alcohol in gelled emulsions for the removal of overpaint during cleaning of oil paintings. Comparative cleaning tests using xanthan gels, Pemulen® TR-2 gels, and neat solvent were made on overpaint on fragments of a seventeenth-century test painting. This approach demonstrated that molecular changes to a benzyl alcohol core resulted in enhanced control during the cleaning process. In some cases a benzyl alcohol derivative enabled selective removal of non-original material, when benzyl alcohol appeared to affect the original paint. Select derivatives were also tested in an area of overpaint on a sixteenth-century oil on panel painting by Jan van Scorel in the Rijksmuseum Collection through modifying the chemical activity of benzyl alcohol. Finally, two GC-MS-based methods were used to monitor benzyl alcohol retention and possible oxidation in paint layers post-treatment.

Abstract: Electron tomography (ET) is an indispensable tool for determining the three-dimensional (3D) structure of nanomaterials in (scanning) transmission electron microscopy ((S)TEM). ET enables 3D characterization of a variety of nanomaterials across different fields, including life sciences, chemistry, solid-state physics, and materials science down to atomic resolution. However, the acquisition of a conventional tilt series for ET is a time-consuming process and thus cannot capture fast transformations of materials in realistic conditions. Moreover, only a limited number of nanoparticles (NPs) can be investigated, hampering a general understanding of the average properties of the material. Therefore, alternative characterization techniques that allow for high-resolution characterization of the surface structure without the need to acquire a full tilt series in ET are required which would enable a more time-efficient investigation with better statistical value. In the first part of this work, an alternative technique for the characterization of the morphology of NPs to improve the throughput and temporal resolution of ET is presented. The proposed technique exploits surface-sensitive secondary electron (SE) imaging in STEM employed using a modification of electron beam-induced current (EBIC) setup. The time- and dose efficiency of SEEBIC are tested in comparison with ET and superior spatial resolution is shown compared to conventional scanning electron microscopy. Finally, contrast artefacts arising in SEEBIC images are described, and their origin is discussed. The second part of my thesis focuses on real applications of the proposed technique and introduces a high-throughput methodology that combines images acquired by SEEBIC with quantitative image analysis to retrieve information about the helicity of gold nanorods. It shows that SEEBIC imaging overcomes the limitation of ET providing a general understanding of the connection between structure and chiroptical properties.

Abstract: Computational fluid dynamics (CFD) applies numerical methods to solve transport phenomena problems. These include, for example, problems related to fluid flow comprising the Navier--Stokes transport equations for either compressible or incompressible fluids together with turbulence models and continuity equations for single and multi-component (reacting and inert) systems. The design space is first segmented into discrete volume elements (meshing). The finite volume method, the subject of this article, discretizes the equations in time and space to produce a set of non-linear algebraic expressions that are assigned to each volume element-cell. The system of equations is solved iteratively with algorithms like the semi-implicit method for pressure-linked equations (SIMPLE) and the pressure implicit splitting of operators (PISO). CFD is especially useful for testing multiple design elements because it is often faster and cheaper than experiments. The downside is that this numerical method is based on models that require validation to check their accuracy. According to a bibliometric analysis, the broad research domains in chemical engineering include: (1) dynamics and CFD-DEM (2) fluid flow, heat transfer and turbulence, (3) mass transfer and combustion, (4) ventilation and environment, and (5) design and optimization. Here, we review the basic theoretical concepts of CFD and illustrate how to set up a problem in the open-source software OpenFOAM to isomerize n-butane to i-butane in a notched reactor under turbulent conditions. We simulated the problem with 1000, 4000, and 16000 cells. According to the Richardson extrapolation, the simulation underestimates the adiabatic temperature rise by 7% with 16000 cells.

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