2, Department of Physics, The University of Texas at Arlington, Arlington, Texas, United States
We present an information-based total-energy optimization method to produce nearly defect-free structural models of amorphous silicon. Using geometrical, structural and topological information from tetrahedral networks, we have shown that it is possible to generate structural configurations of amorphous silicon, which are superior than the models obtained from conventional reverse Monte Carlo methods involving structural constraints and total-energy optimization. The new static (i.e. relaxation-based) approach presented here is capable of producing atomistic models with structural properties which are on a par with those obtained from the modified Wooten-Winer-Weaire (WWW) models of amorphous silicon. Structural, electronic, and vibrational properties of the hybrid models are compared with the best dynamical models obtained from using machine-intelligence-based algorithms and efficient molecular-dynamics simulations, reported in the recent literature. We have shown that, together with the WWW models, our hybrid models represent one of the best static models so far produced by total-energy-based Monte Carlo methods in conjunction with experimental diffraction data of amorphous silicon.