This Collection supports and amplifies research related to SDG 9 - Industry, Innovation & Infrastructure. Discovering new materials with customizable and optimized properties, driven either by ...

In the age of digital transformation, machine learning (ML) is rapidly becoming a pivotal technology in various sectors. One of its most exciting applications is in the field of advanced materials ...

Technologies that underpin modern society, such as smartphones and automobiles, rely on a diverse range of functional ...

Key TakeawaysThe Materials Project is the most-cited resource for materials data and analysis tools in materials science.The ...

Machine learning is transforming many scientific fields, including computational materials science. For about two decades, scientists have been using it to make accurate yet inexpensive calculations ...

A team of researchers has successfully predicted abnormal grain growth in simulated polycrystalline materials for the first time -- a development that could lead to the creation of stronger, more ...

Dhruv Shenai investigates how machine learning and lab automation are transforming materials science at Cambridge ...

A recent study published in Small highlights how machine learning (ML) is reshaping the search for sustainable energy materials. Researchers introduced OptiMate, a graph attention network designed to ...

Shanghai, August 21, 2025 — Nuclear energy is widely recognized as one of the most promising clean energy sources for the future, but its safe and efficient use depends critically on the development ...

Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...

Literature searches, simulations, and practical experiments have been part of the materials science toolkit for decades, but the last few years have seen an explosion of machine learning-driven ...