Machine learning takes materials modeling into new era

The arrangement of electrons in matter, known as electronic structure, plays a critical role in fundamental and applied research such as drug design and energy storage. However, the lack of a simulation technique that provides both high fidelity and scalability across different time and length scales has long been an obstacle to the progress of these technologies. We have developed a machine learning method – the Materials Learning Algorithms (MALA) – that replaces traditional electronic structure simulation techniques. MALA enables electronic structure simulations at previously unattainable length scales.

Read more about this in the press release.