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 ...

From predicting properties before a material even exists to designing entirely new structures, AI is becoming the ultimate lab partner for materials scientists. Machine learning models are ...

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 ...

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

Cosmic-ray muon sources exhibit distinct scattering angle distributions when interacting with materials of different atomic numbers (Z values), facilitating the identification of various Z-class ...

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

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