Constrained evolutionary algorithm for structure prediction of molecular crystals: methodology and applications

TL;DR

This paper introduces a specialized evolutionary algorithm for predicting complex molecular crystal structures by treating molecular units as whole entities, significantly reducing search space and improving efficiency.

Contribution

The paper presents a novel evolutionary algorithm that treats molecular units as whole, with new variation operators, enhancing structure prediction efficiency for complex crystals.

Findings

Successfully predicts structures of various molecular crystals.

Efficiently predicts methane A with 105 atoms per unit cell.

Demonstrates applicability to complex inorganic crystals.

Abstract

Evolutionary crystal structure prediction proved to be a powerful approach for studying a wide range of materials. Here, we present a specifically designed algorithm for the prediction of the structure of complex crystals consisting of well-defined molecular units. The main feature of this new approach is that each unit is treated as a whole body, which drastically reduces the search space and improves the efficiency, but necessitates the introduction of new variation operators described here. To increase diversity of the population of structures, the initial population and part($\scriptsize{\sim}$20%) of the new generations are generated using space group symmetry combined with random cell parameters and random positions and orientations of molecular units. We illustrate the efficiency and reliability of this approach by number of tests (ice, ammonia, carbon dioxide, methane, benzene, glycine and butane-1,4-diammonium dibromide). This approach easily predicts the crystal structure of methane \emph{A} containing 21 methane molecules (105 atoms) per unit cell. We demonstrate that this new approach has also a high potential for the study of complex inorganic crystals on the examples of a complex hydrogen storage material Mg(BH$_4$)$_2$ and elemental boron.