Researchers from Google DeepMind, BIFOLD, and TU Berlin have unveiled AI models that simulate molecular behavior without hard-coded physical laws, achieving competitive results through massive ...

A universal potential for all-purpose atomic simulations has been pursued for decades, but remains challenging due to limitations in model expressiveness and dataset construction. Now, writing in the ...

What is the speed and timing of the Earth’s inner core cooling? This is what a recent study published in Nature Communications hopes to address as a team of scientists investigated the composition ...

Google DeepMind and collaborators have developed Euclidean Fast Attention (EFA), a machine learning method that more efficiently models global atomic interactions in complex chemical systems. This ...

Atomic simulation serves as an indispensable microscope for modern science, bridging the gap between theoretical predictions and experimental results. However, the field has historically been ...

The background: To understand how complex materials behave at the atomic level, physicists calculate what are known as ...