Theoretical Study on Inner Shell Electron Impact Excitation of Lithium

Cross sections for electron impact excitation of lithium from the ground state 1s(2)2s to the excited states 1s2s(2), 1s2p(2), 1s2snp (n = 2-5), 1s2sns (n = 3-5), 1s2pns (n = 3-5), and 1s2pnp (n = 3-5) are calculated by using a full relativistic distorted wave method. The latest experimental electron energy loss spectra for inner-shell electron excitations of lithium at a given incident electron energy of 2500 eV [Chin. Phys. Lett. 25 (2008) 3649] have been reproduced by the present theoretical investigation excellently. At the same time, the structures of electron energy loss spectra of lithium at low incident electron energy are also predicted theoretically, it is found that the electron energy loss spectra in the energy region of 55-57 eV show two-peak structures.

Differential and Integral Cross Sections for Electron Impact Excitation of Lithium

The differential and integral cross sections for electron impact excitation of lithium from the ground state 1s(2)2s to excited states 1s(2)2p, 1s(2)3l (l = s,p,d) and 1s(2)4l (l = s,p,d,f) at incident energies ranging from 5 eV to 25 eV are calculated by using a full relativistic distorted wave method. The target state wavefunctions are calculated by using the Grasp92 code. The continuum orbitals are computed in the distorted-wave approximation, in which the direct and exchange potentials among all the electrons are included. A part of the cross sections are compared with the available experimental data and with the previous theoretical values. It is found that, for the integral cross sections, the present calculations are in good agreement with the time-independent distorted wave method calculation, for differential cross sections, our results agree with the experimental data very well.

Electrolytic Deposition and Diffusion of Lithium onto Magnesium-9 Wt Pct Yttrium Bulk Alloy in Low-Temperature Molten Salt of Lithium Chloride and Potassium Chloride

The electrolytic deposition and diffusion of lithium onto bulk magnesium-9 wt pct yttrium alloy cathode in molten salt of 47 wt pct lithium chloride and 53 wt pct potassium chloride at 693 K were investigated. Results show that magnesium-yttrium-lithium ternary alloys are formed on the surface of the cathodes, and a penetration depth of 642 mu m is acquired after 2 hours of electrolysis at the cathodic current density of 0.06 A center dot cm(-2). The diffusion of lithium results in a great amount of precipitates in the lithium containing layer. These precipitates are the compound of Mg41Y5, which arrange along the grain boundaries and hinder the diffusion of lithium, and solid solution of yttrium in magnesium. The grain boundaries and the twins of the magnesium-9 wt pct yttrium substrate also have negative effects on the diffusion of lithium.

Structure-activity relationship of surfactant for preparing DMFC anodic catalyst

Three kinds of surfactants as stabilizer were applied to the preparation of electrocatalysts for direct methanol fuel cell (DMFC). The catalysts have been characterized by examining their catalytic activities, morphologies and particle sizes by means of cyclic voltammetry, chronoamperometry, X-ray diffraction and transmission electron microscopy (TEM). It is found that the surfactants with different structures have a significantly influence on the catalyst shape and activity. The catalysts prepared with non-ionic surfactants as the stabilizer show higher activity for direct oxidation of methanol. The structure-activity relationship (SAR) analysis has been explored and the effect of hydrophile-lipophile balance (HLB value) has also been discussed.

Applications of the method of three-dimensional projection of a molecule in quantitative structure-activity relationship of phenol derivatives

Five variables for phenol derivatives were calculated by molecular projection in three-dimensional space which were combined with eight quantum-chemical parameters and three Am indices. These variables were selected by using leaps-and-bounds regression analysis. Multiple linear regression analysis and artificial neural networks' were performed, and the results obtained by using. artificial neural networks are superior than that obtained by using multiple linear regression.