Artificial intelligence (AI) is being increasingly integrated into scientific discovery to augment
and accelerate research, helping scientists to generate hypotheses, design experiments …

Small data are often used in scientific and engineering research due to the presence of
various constraints, such as time, cost, ethics, privacy, security, and technical limitations in …

Transitioning from fossil fuels to renewable energy sources is a critical global challenge; it
demands advances—at the materials, devices and systems levels—for the efficient …

Networks—or graphs—are universal descriptors of systems of interacting elements. In
biomedicine and healthcare, they can represent, for example, molecular interactions …

We use prompt engineering to guide ChatGPT in the automation of text mining of metal–
organic framework (MOF) synthesis conditions from diverse formats and styles of the …

Traditional computational approaches to design chemical species are limited by the need to
compute properties for a vast number of candidates, eg, by discriminative modeling …

Artificial intelligence (AI) has the potential to revolutionize the drug discovery process,
offering improved efficiency, accuracy, and speed. However, the successful application of AI …

High-entropy alloys are solid solutions of multiple principal elements that are capable of
reaching composition and property regimes inaccessible for dilute materials. Discovering …

Over the last decades, excellent computational chemistry tools have been developed.
Integrating them into a single platform with enhanced accessibility could help reaching their …

Deep learning (DL) is one of the fastest-growing topics in materials data science, with
rapidly emerging applications spanning atomistic, image-based, spectral, and textual data …