One of the most exciting tools that have entered the material science toolbox in recent years
is machine learning. This collection of statistical methods has already proved to be capable …

Advances in machine learning have impacted myriad areas of materials science, such as
the discovery of novel materials and the improvement of molecular simulations, with likely …

Solutions to many of the world's problems depend upon materials research and
development. However, advanced materials can take decades to discover and decades …

This Methods/Protocols article is intended for materials scientists interested in performing
machine learning-centered research. We cover broad guidelines and best practices …

The advent of big data and algorithmic developments in the field of machine learning (and
artificial intelligence, in general) have greatly impacted the entire spectrum of physical …

Exploding data volumes and velocities, new computational methods and platforms, and
ubiquitous connectivity demand new approaches to computation in the sciences. These new …

High-level programming languages such as Python are increasingly used to provide
intuitive interfaces to libraries written in lower-level languages and for assembling …

High-fidelity computer-aided experimentation is becoming more accessible with the
development of computing power and artificial intelligence tools. The advancement of …

Nuclear materials are often demanded to function for extended time in extreme
environments, including high radiation fluxes with associated transmutations, high …

Companies struggle to continuously develop and deploy Artificial Intelligence (AI) models to
complex production systems due to AI characteristics while assuring quality. To ease the …