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 ...

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, ...

Engineers at NIMS Develop a System That Captures All the Elements of Trial and Error in Material Design, Enabling Reliable ...

The field of industrial production is increasingly dependent on materials whose origins and behaviors are intricately tied to geological processes and ...

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 ...

Recent advances in large-scale AI models, including large language and vision-language-action models, have significantly expanded the capabilities of ...

Discovering and characterizing new materials is important for unlocking advances in fields like clean energy, advanced ...