Genetic Algorithms For Structure Prediction Of New Bithiazole Molecular Crystals Methodology And Applications

Abstract

This article describes the application of our distributed computing framework for crystal structure prediction (CSP), the modified genetic algorithms for crystal and cluster prediction (MGAC), to predict the crystal structure of bithiazole molecules. Using a distributed parallel genetic algorithm and local energy minimization of the structures followed by the classifying, sorting, and archiving of the most relevant structures. A genetic algorithm has been used to generate plausible crystal structures from the knowledge of only the unit cell dimensions and constituent elements. This strategy increases the efficiency of the DFT based GA by several orders of magnitude. This gain allows considerable increase in size and complexity of systems that can be studied by first principles. The Gaussian 03 package is used to perform the calculation of these atomic charges at the optimized geometry (HF/6-31G*level).Our results indicate that the method can consistently find the experimentally known crystal structures of bithiazole molecules. The structural of computational parameters are in agreement with the experimental data.