Materials databases lie at the heart of future data-driven discovery in energy-related fields, say researchers from Tohoku ...

(Nanowerk Spotlight) Computational calculations are revolutionizing modern scientific research, offering a powerful means to predict the potential applications of new materials. Unlike traditional ...

Machine learning is transforming many scientific fields, including computational materials science. For about two decades, scientists have been using it to make accurate yet inexpensive calculations ...

Found in knee replacements and bone plates, aircraft components, and catalytic converters, the exceptionally strong metals known as multiple principal element alloys (MPEA) are about to get even ...

A firefly-inspired AI framework makes atomic structure prediction more robust by combining multimodal search with an ...

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 ...

The diagram illustrates the interplay among data acquisition, machine learning, and experiment synthesis. Physical models such as thermodynamics and kinetics can be integrated into ML models as expert ...

Northwestern Engineering’s Chris Wolverton has been named a fellow of the Materials Research Society for his pioneering work in computational materials science for materials design and discovery, ...

This workshop on Autonomous Materials Science will discuss where the weak links are in future systems that will reduce, and eventually eliminate, the need for human intervention in the design and ...

The Arkansas Integrative Metabolic Research Center will host Dr. Prateek Verma, manager of the AIMRC Data Science Core, Wednesday, April 1, to highlight the unique complex-analysis and ...