(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 ...

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, ...

(a) A feasible route for developing large materials models capable of describing the structure-property relationship of materials. The universal materials model of DeepH accepts an arbitrary material ...

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 ...

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 ...

Modeling and creating simulations are key skills in any math, science or engineering profession. That’s why we’ve created a unique, interdisciplinary computational science minor. This minor gives ...

Building large-scale quantum technologies requires reliable ways to connect individual quantum bits (qubits) without destroying their fragile quantum states. In a new theoretical study, published in ...

A Frontier of Physics and Material Science Exploring New Phases of Matter. We’re living in a pretty exciting time for ...