Abstract: Methane needle-plane discharge has practical application prospect and scientific research significance since methane conversion heavy oil hydrogenation is formed by coupling methane needle-plane discharge with heavy oil hydrogenation, which can achieve high-efficient heavy oil hydrogenation and increase the yields of high value-added light olefins. In this paper, a two-dimensional fluid model is built up for numerically simulating the methane needle-plane discharge plasma at atmospheric pressure. Spatial and axial distributions of electric intensity, electron temperature and particle densities are obtained. Reaction yields are summarized and crucial pathways to produce various kinds of charged and neutral particles are found out. Simulation results indicate that axial evolutions of CH3+ and CH4+ densities, electric intensity and electron temperature are similar and closely related. The CH5+ and C2H5+ densities first increase and then decrease along the axial direction. The CH3 and H densities have nearly identical spatial and axial distributions. Particle density distributions of CH2, C2H4 and C2H5 are obviously different in the area near the cathode but comparatively resemblant in the positive column region. The CH3+ and CH4+ are produced by electron impact ionizations between electrons and CH4. The CH5+ and C2H5+ are respectively generated by molecular impact dissociations between CH3+ and CH4 and between CH4+ and CH4. Electron impact decomposition between electrons and CH4 is a dominated reaction to produce CH3, CH2, CH and H. The reactions between CH2 and CH4 and between electrons and C2H4 are critical pathways to produce C2H4 and C2H2, respectively. In addition, the yields of electron impact decomposition reactions between electrons and CH4 and reactions between CH2 and CH4 account for 52.15% and 47.85% of total yields of H-2 respectively.

Abstract: Plasma bioscience and medicine are both rapidly growing fields. Their aim is to utilize cold physical plasmas for desired biological outcomes in medicine, biotechnology, agriculture, and general hygienic purposes. Great success has been achieved in many applications with individually designed plasma sources and plasma parameters. Although lab and application-specific tuning of plasmas is a great advantage of this technology, standardized units to define plasma treatments are required to facilitate comparison of the effects found by different researchers who do not use the same plasma sources. By drawing conclusions from over a century of plasma biomedical research, we propose that all researchers adopt the use of a standardized value, the plasma treatment unit (PTU), to describe the biological effects of different cold plasma sources and treatment regimens. It quantifies a key plasma effector in biological systems as an indicator and may provide the foundation for an analogous and clinically relevant unit in the future.

Abstract: A quantitative HPLC method was applied to determine the amounts of C-60 and C-70 present in extracts of soot produced in the electric arc reactor and in flames. The combustion method was found to yield a higher C-70/C-60 ratio (0.67) compared with the evaporation experiment where the C-70/C-60 ratio amounts to 0.27.

Abstract: Submicron colloidal Ag particles and nano-sized filaments forming a statistical percolation network during ''in situ'' development of double structure tabular microcrystals of AgRr(I) emulsions have been studied by electron energy-loss spectroscopy and zero-loss electron spectroscopic imaging (EELS/ZLESI). Image analysis has shown that random quasi-fractal clusters were formed in the colloid. ZLESI has been applied to characterise the morphology and defect structure of aggregated particles and filaments. Their energy-loss spectra revealed plasmon excitations and interband 4d electron transitions between 4-32 eV energy-loss. To study the cluster structure and its relation to the physical properties, fractal analysis including estimations of cluster fractal dimensions and of density autocorrelation functions has been performed. Mechanisms of fractal aggregation based on known models of diffusion limited aggregation, cluster-cluster aggregation and percolation are discussed.