Molecular dynamics studies on dislocations in crystallites of nanocrystalline alpha-iron

Molecular dynamics simulations have been carried our to study the atomic structure of the crystalline component of nanocrystalline alpha-iron. A two-dimensional computational block is used to simulate the consolidation process. It is found that dislocations are generated in the crystallites during consolidation when the grain size is large enough. The critical value of the grain size for dislocation generation appears to be about 9 nm. This result agrees with experiment qualitatively. AN dislocations that are preset in the original grains glide out during consolidation. It shows that dislocations in the crystallites we generated in consolidation process, but not in the original grains. Higher consolidation pressure results in more dislocations. Furthermore, new interfaces are found within crystallites. These interfaces might result from the special environment of nanomaterial. (C) 1998 Acta Metallurgica Inc.

Comparative studies on parallel and antiparallel duplex and triplex DNA

Parallel strand models for base sequences d(A)(10). d(T)(10), d(AT)(5) . d(TA)(5), d(G(5)C(5)). d(C(5)G(5)), d(GC)(5) . d(CG)(5) and d(CTATAGGGAT). d(GATATCCCTA), where reverse Watson-Crick A-T pairing with two H-bonds and reverse Watson-Crick G-C pairing with one H-bond or with two H-bonds were adopted, and three models of d(T)(14). d(A)(14). d(T)(14) triple helix with different strand orientations were built up by molecular architecture and energy minimization. Comparisons of parallel duplex models with their corresponding B-DNA models and comparisons among the three triple helices showed: (i) conformational energies of parallel AT duplex models were a little lower, while for GC duplex models they were about 8% higher than that of their corresponding B-DNA models; (ii) the energy differences between parallel and B-type duplex models and among the three triple helices arose mainly from base stacking energies, especially for GC base pairing; (iii) the parallel duplexes with one H-bond G-C pairs were less stable than those with two H-bonds G-C pairs. The present paper includes a brief discussion about the effect of base stacking and base sequences on DNA conformations. (C) 1997 Academic Press Limited.

Kinetic Studies of Gas Flows

Our recent studies on kinetic behaviors of gas flows are reviewed in this paper. These flows have a wide range of background, but share a common feature that the flow Knudsen number is larger than 0.01. Thus kinetic approaches such as the direct simulation Monte Carlo method are required for their description. In the past few years, we studied several micro/nano-scale flows by developing novel particle simulation approach, and investigated the flows in low-pressure chambers and at high altitude. In addition, the microscopic behaviors of a couple of classical flow problems were analyzed, which shows the potential for kinetic approaches to reveal the microscopic mechanism of gas flows.

Effective descriptions of molecular structures and the quantitative structure - Activity relationship studies

In this research. we found CoMFA alone could not obtain sufficiently a strong equation to allow confident prediction for aminobenzenes. When some other parameter. such as heat of molecular formation of the compounds, was introduced into the CoMFA model, the results Were improved greatly. It gives us a hint that a better description for molecular structures will yield a better prediction model, and this hint challenged us to look for another method-the projection areas of molecules in 3D space for 3D-QSAR. It is surprising that much better results than that obtained by using CoMFA Were achieved. Besides the CoMFA analysis. multiregression analysis and neural network methods for building the models were used in this paper.

Quantitative structure-property relationships for colour reagents and their colour reactions with cerium using computational neural networks

Quantitative structure-activity/property relationships (QSAR/QSPR) studies have been exploited extensively in the designs of drugs and pesticides, but few such studies have been applied to the design of colour reagents. In this work, the topological indices A(x1)-A(x3) suggested in this laboratory were applied to multivariate analysis in structure-property studies. The topological indices of 43 phosphone bisazo derivatives of chromotropic acid were calculated. The structure-property relationships between colour reagents and their colour reactions with cerium were studied using A(x1-Ax3) indices with satisfactory results. The purpose of this work was to establish whether QSAR can be used to predict the contrasts of colour reactions and in the longer term to be a helpful tool in colour reagent design.

Quantitative structure-property relationships for colour reagents and their colour reactions with ytterbium using regression analysis and computational neural networks

In this paper, the new topological indices A(x1)-A(x3) suggested in our laboratory and molecular connectivity indices have been applied to multivariate analysis in structure-property studies. The topological indices of twenty asymmetrical phosphono bisazo derivatives of chromotropic acid have been calculated. The structure-property relationships between colour reagents and their colour reactions with ytterbium have been studied by A(x1)-A(x3) indices and molecular connectivity indices with satisfactory results. Multiple regression analysis and neural networks were employed simultaneously in this study.

Algorithm Studies on How to Obtain a Conditional Nonlinear Optimal Perturbation (CNOP)

The conditional nonlinear optimal perturbation (CNOP), which is a nonlinear generalization of the linear singular vector (LSV), is applied in important problems of atmospheric and oceanic sciences, including ENSO predictability, targeted observations, and ensemble forecast. In this study, we investigate the computational cost of obtaining the CNOP by several methods. Differences and similarities, in terms of the computational error and cost in obtaining the CNOP, are compared among the sequential quadratic programming (SQP) algorithm, the limited memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) algorithm, and the spectral projected gradients (SPG2) algorithm. A theoretical grassland ecosystem model and the classical Lorenz model are used as examples. Numerical results demonstrate that the computational error is acceptable with all three algorithms. The computational cost to obtain the CNOP is reduced by using the SQP algorithm. The experimental results also reveal that the L-BFGS algorithm is the most effective algorithm among the three optimization algorithms for obtaining the CNOP. The numerical results suggest a new approach and algorithm for obtaining the CNOP for a large-scale optimization problem.