More than 20 faculty members and several students from across academic disciplines attended a two-day training workshop on June 4–5 to learn how AI machine-learning skills can assist with their ...

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 organic materials ...

Electron density prediction for a four-million-atom aluminum system using machine learning, deemed to be infeasible using traditional DFT method. × Researchers from Michigan Tech and the University of ...

An AI approach developed by researchers from the University of Sheffield and AstraZeneca, could make it easier to design proteins needed for new treatments. Inverse protein folding is a critical ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...

Materials testing remains a cornerstone of engineering and manufacturing, ensuring that components and structures—from ...

MIT researchers created a technique that captures chemical arrangements across materials to improve predictions of how metal ...