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 ...

A research team has successfully developed a technology that utilizes Large Language Models (LLMs) to predict the synthesizability of novel materials and interpret the basis for such predictions. The ...

For thousands of these materials, X-ray diffraction patterns exist but remain unsolved. To try to crack the structures of these materials, Freedman and her colleagues trained a machine-learning model ...

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 ...

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 ...

Engineers at NIMS Develop a System That Captures All the Elements of Trial and Error in Material Design, Enabling Reliable Reproduction of the Reasoning Processes and Results TSUKUBA, JAPAN - April 22 ...

A new wave of physics-informed AI is accelerating the way scientists design and understand advanced materials. By embedding physical laws into machine learning models, researchers can simulate, test, ...