Editor's choice: Machine learning for material discovery, design and characterisation

Machine learning has been rapidly developing in the past decade and has become an important tool to the scientific community. Publicly available datasets can be exploited to automate the discovery of new materials, bringing unlikely solutions to material problems to our attention in a way that human researchers might be unable, or unlikely, to spot. Machine learning techniques can be applied not only to the discovery of materials, but also to design devices or characterise materials from images or limited datasets. Here, we present a number of publications in Scientific Reports that highlight the achievements of researchers in this area.

Closeup network connection on a blurred network background.

Materials Discovery

Automated Characterization

Novel Framework

Property Prediction