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 ...

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

Large language models are powering a new generation of AI agents that could transform computational chemistry from a ...

Machine learning interatomic potentials (MLIPs) have become an essential tool to enable long-time scale simulations of materials and molecules at unprecedented accuracies. The aim of this collection ...

The team developed a computational framework using robotic path planning algorithms to rapidly identify optimal composition gradients between dissimilar materials. The framework enables the creation ...

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, ...

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 ...

Computational Materials Discovery has emerged as one of the important tools available to chemists, physicists, and materials scientists to produce designer materials with superior performance. They ...

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 ...

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 ...