Origin of antiferromagnetism in CoO: A density functional theory study

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Correcting the systematic error of the density functional theory calculation: the alternate combination approach of genetic algorithm and neural network

The alternate combinational approach of genetic algorithm and neural network (AGANN) has been presented to correct the systematic error of the density functional theory (DFT) calculation. It treats the DFT as a black box and models the error through external statistical information. As a demonstration, the AGANN method has been applied in the correction of the lattice energies from the DFT calculation for 72 metal halides and hydrides. Through the AGANN correction, the mean absolute value of the relative errors of the calculated lattice energies to the experimental values decreases from 4.93% to 1.20% in the testing set. For comparison, the neural network approach reduces the mean value to 2.56%. And for the common combinational approach of genetic algorithm and neural network, the value drops to 2.15%. The multiple linear regression method almost has no correction effect here.

Investigation of Interfacial Tensions for Carbon Dioxide Aqueous Solutions by Perturbed-Chain Statistical Associating Fluid Theory Combined with Density-Gradient Theory

The perturbed-chain statistical associating fluid theory and density-gradient theory are used to construct an equation of state (EOS) applicable for the phase behaviors of carbon dioxide aqueous solutions. With the molecular parameters and influence parameters respectively regressed from bulk properties and surface tensions of pure fluids as input, both the bulk and interfacial properties of carbon dioxide aqueous solutions are satisfactorily correlated by adjusting the binary interaction parameter (k(ij)). Our results show that the constructed EOS is able to describe the interfacial properties of carbon dioxide aqueous solutions in a wide temperature range, and illustrate the influences of temperature, pressure, and densities in each phase on the interfacial properties.

Energy level analyses of even-parity J=1 and 2 Rydberg states of Sn I by multichannel quantum defect theory

This paper analyzes the energy levels along the even-parity J=1 and 2 Rydberg series of Sn I by multichannel quantum defect theory. A good agreement between theoretical and experimental energy levels was achieved. Below 59198 cm~(-1), a total of 85 and 23 new energy levels, respectively, in the J=1 and J=2 series, which cannot be measured previously by experiments, are predicted in this work. Based on the calculated admixture coefficients of each channel, interchannel interactions were discussed in detail. The results are helpful to understand the characteristics of configuration interaction among even-parity levels in Sn I.

Properties and structure of N = Z nuclei within relativistic mean field theory

The axially deformed relativistic mean field theory with the force NLSH has been performed in the blocked BCS approximation to investigate the proper-ties and structure of N=Z nuclei from Z=20 to Z=48. Some ground state quantities such as binding energies, quadrupole deformations, one/two-nucleon separation energies, root-mean-squaxe (rms) radii of charge and neutron, and shell gaps have been calculated. The results suggest that large deformations can be found in medium-heavy nuclei with N=Z=38-42. The charge and neutron rms radii increase rapidly beyond the magic number N=Z=28 until Z=42 with increasing nucleon number, which is similar to isotope shift, yet beyond Z=42, they decrease dramatically as the structure changes greatly from Z=42 to Z=43. The evolution of shell gaps with proton number Z can be clearly observed. Besides the appearance of possible new shell closures, some conventional shell closures have been found to disappear in some region. In addition, we found that the Coulomb interaction is not strong enough to breakdown the shell structure of protons in the current region.

A spatial sampling optimization package using MSN theory

The density and distribution of spatial samples heavily affect the precision and reliability of estimated population attributes. An optimization method based on Mean of Surface with Nonhomogeneity (MSN) theory has been developed into a computer package with the purpose of improving accuracy in the global estimation of some spatial properties, given a spatial sample distributed over a heterogeneous surface; and in return, for a given variance of estimation, the program can export both the optimal number of sample units needed and their appropriate distribution within a specified research area. (C) 2010 Elsevier Ltd. All rights reserved.