Advanced algorithms and hardware acceleration Deep learning models for predicting properties, optimizing structures, and discovering new materials are being paired with hardware accelerators like GPUs ...
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 ...
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 ...
Open Materials 2024 will be one of the biggest data sets available for materials science. Meta is releasing a massive data set and models, called Open Materials 2024, that could help scientists use AI ...
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 ...
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 ...
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