Combining materials science, artificial intelligence (AI), physical chemistry, and other
disciplines, materials informatics is continuously accelerating the vigorous development of …

Materials informatics has been gaining popularity with the rapid development of
computational materials science. However, collaborations between information science and …

As an implementation tool of data intensive scientific research methods, machine learning
(ML) can effectively shorten the research and development (R&D) cycle of new materials by …

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 …

Artificial intelligence (AI) is gaining strength, and materials science can both contribute to
and profit from it. In a simultaneous progress race, new materials, systems, and processes …

Material science has historically evolved in tandem with advancements in technologies for
characterization, synthesis, and computation. Another type of technology to add to this mix is …

The goal of the Materials Genome Initiative is to substantially reduce the time and cost of
materials design and deployment. Achieving this goal requires taking advantage of the …

In recent years materials informatics, which is the application of data science to problems in
materials science and engineering, has emerged as a powerful tool for materials discovery …

Artificial intelligence (AI) has received widespread attention over the last few decades due to
its potential to increase automation and accelerate productivity. In recent years, a large …

We are excited to present this Special Topic collection on Machine Learning for Materials
Design and Discovery in the Journal of Applied Physics. With a wide range of exciting and …