Machine learning is transforming many scientific fields, including computational materials science. For about two decades, ...

In this workflow, nanoreactor simulations automatically sample reactive chemical space without relying on human intuition. The nanoreactor is a special class of atomistic simulations in which chemical ...

Researchers have used machine learning to create a model that simulates reactive processes in organic materials and conditions. Researchers from Carnegie Mellon University and Los Alamos National ...

Harvard researchers bring the accuracy, sample efficiency, and robustness of deep equivariant neural networks to the simulate 44 million atoms. This is achieved through a combination of innovative ...

If scientists could better predict how heat moves through semiconductors and insulators, they could design more efficient power generation systems. However, the thermal properties of materials can be ...

(Nanowerk News) Researchers from Carnegie Mellon University and Los Alamos National Laboratory have used machine learning to create a model that can simulate reactive processes in a diverse set of ...