The age of cognitive computing and artificial intelligence (AI) is just dawning. Inspired by its
successes and promises, several AI ecosystems are blossoming, many of them within the …

Batteries are of paramount importance for the energy storage, consumption, and
transportation in the current and future society. Recently machine learning (ML) has …

Active learning—the field of machine learning (ML) dedicated to optimal experiment design—
has played a part in science as far back as the 18th century when Laplace used it to guide …

In metals additive manufacturing (AM), materials and components are concurrently made in
a single process as layers of metal are fabricated on top of each other in the near-final …

This perspective provides an experimentalist's view on materials discovery in multinary
materials systems—from nanoparticles over thin films to bulk—based on combinatorial thin …

This chapter addresses the role that data‐driven approaches, especially machine learning
methods, are expected to play in materials research in the immediate future. Machine …

The Materials Genome Initiative, a national effort to introduce new materials into the market
faster and at lower cost, has made significant progress in computational simulation and …

Since its widespread use in concrete began over 100 years ago, the chemical composition
and physical properties of portland cement have changed only incrementally in response to …

Quantum mechanics‐based ab initio molecular dynamics (MD) simulation schemes offer an
accurate and direct means to monitor the time evolution of materials. Nevertheless, the …

Rational materials design based on prior knowledge is attractive because it promises to
avoid time-consuming synthesis and testing of numerous materials candidates. However …