Calculation of Au surface energy by molecular dynamics combined with neural networks
Xiang-feng Guan · The Chinese Journal of Nonferrous Metals · 2005
Via embedded-atom model and molecular dynamics simulation, the surface energies of three low-index and some high-index planes were calculated for precious metal Au, and the error back-propagation network (BP) developed by Levenberg-Marquardt algorithm was adopted. Combining the data calculated with the molecular dynamics model, a great deal of data were trained many times and compared with the calculated data, and the prediction of high-index surface energy was performed. The results show that the method has high predicting accuracy. The order of the three low-index planes was predicted exactly. The surface energies on the other planes show a tendency that first increasing and then decreasing with angle between the planes and (111) plane increasing.