Recent advances in experimental and computational methods are increasing the quantity
and complexity of generated data. This massive amount of raw data needs to be stored and …

Abstract Machine learning (ML) is rapidly revolutionizing many fields and is starting to
change landscapes for physics and chemistry. With its ability to solve complex tasks …

Predicting the stability of the perovskite structure remains a long-standing challenge for the
discovery of new functional materials for many applications including photovoltaics and …

Progress in the discovery of new materials has been accelerated by the development of
reliable quantum-mechanical approaches to crystal structure prediction. The properties of a …

Knowledge and foundational understanding of phenomena associated with the behavior of
materials at the nanoscale is one of the key scientific challenges toward a sustainable …

We present new developments of the evolutionary algorithm USPEX for crystal structure
prediction and its adaptation to cluster structure prediction. We show how to generate …

The high pressure structures, metallization and superconductivity of recently synthesized H2-
containing compounds (H2S) 2H2 are elucidated by ab initio calculations. The ordered …

Hardness can be defined microscopically as the combined resistance of chemical bonds in
a material to indentation. The current review presents three most popular microscopic …

Pressure‐stabilized hydrides are a new rapidly growing class of high‐temperature
superconductors, which is believed to be described within the conventional phonon …

Here we report the high-pressure synthesis of a series of lanthanum–yttrium ternary
hydrides obtained at pressures of 170–196 GPa via the laser heating of P6 3/mmc La–Y …