New technique sharpens predictions of metal alloy behavior by capturing subtle atomic patterns

Companies working at the frontier of aerospace, energy and computing are constantly looking for new materials to improve performance. But in order to understand how those materials will actually ...
Nature

Enhancing transferability of machine learning-based polarizability models in condensed-phase systems via atomic polarizability constraint

Accurate prediction of molecular polarizability is essential for understanding electrical, optical, and dielectric properties of materials. Traditional quantum mechanical (QM) methods, though precise ...
Nature

Automated model building and protein identification in cryo-EM maps

Interpreting electron cryo-microscopy (cryo-EM) maps with atomic models requires high levels of expertise and labour-intensive manual intervention in three-dimensional computer graphics programs 1,2.