Machine learning is transforming many scientific fields, including computational materials science. For about two decades, ...

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 ...

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 ...

Open Materials 2024 will be one of the biggest data sets available for materials science. Meta is releasing a massive data set and models, called Open Materials 2024, that could help scientists use AI ...

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 ...

At Northwestern University, our first-of-its-kind materials science department collaborates extensively with our leading mechanical engineering department, resulting in a strong history of ...