Designing materials with advanced functionalities is the main focus of contemporary solid-
state physics and chemistry. Research efforts worldwide are funneled into a few high-end …

Crystal structure predictions based on first-principles calculations have gained great
success in materials science and solid state physics. However, the remaining challenges …

We propose a methodology for crystal structure prediction that is based on the evolutionary
algorithm USPEX and the machine-learning interatomic potentials actively learning on-the …

Predicting crystal structure has always been a challenging problem for physical sciences.
Recently, computational methods have been built to predict crystal structure with success …

The theoretical exploration of the phase diagrams of binary hydrides under pressure using
ab initio crystal structure prediction techniques coupled with first principles calculations has …

Transition metal nitrides have been suggested to have both high hardness and good
thermal stability with large potential application value, but so far stable superhard transition …

Evolutionary algorithms (EAs) are robust stochastic optimisers that perform well over a wide
range of problems. Their robustness, however, may be affected by several adjustable …

We systematically investigated the potential of single-layer VS2 polytypes as Na-battery
anode materials via density functional theory calculations. We found that sodiation tends to …

Significant progress has been made in the field of a priori crystal structure prediction, with a
number of recent remarkable success stories. Herein, we briefly outline the methods that …

Over the past decade, a combination of crystal structure prediction techniques and
experimental synthetic work has thoroughly explored the phase diagrams of binary hydrides …