Efficient perturbations for basin hopping in amorphous glasses

Abstract

Efficient exploration of the complex potential-energy landscapes of amorphous materials is central to computational structure discovery and refinement. Conventional Monte Carlo, reverse Monte Carlo, and related methods typically sample configuration space through small, local trial moves and may require millions to tens of millions of moves to converge. Here, we evaluate larger, nonlocal perturbations followed by local geometry relaxation as an alternative sampling strategy. We develop and test four perturbation types using amorphous Al$_2$O$_3$ as a model system. Among them, moving an oxygen atom to change the coordination numbers of two aluminum atoms, allows access to low-energy configurations with substantially fewer trial moves than a conventional Monte Carlo trajectory. These results suggest that relaxation-assisted nonlocal moves could reduce trapping in local minima and improve sampling in structure-search and reverse Monte Carlo workflows.