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 ...
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AI-based model measures atomic defects in materials
In biology, defects are generally bad. But in materials science, defects can be intentionally tuned to give materials useful new properties. Today, atomic-scale defects are carefully introduced during ...
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Physics-trained AI models speed up engineering simulations and design work
Running a single physics simulation can take hours or days, depending on the complexity of the geometry and the equations ...
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 ...
Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...
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 ...
Researchers from the University of South China and Purdue University have developed ultra-high strength, high-ductility steel ...
As AI's integration in the process of designing and improving industrial infrastructure progresses, governance needs to ...
A new study shows that combining machine learning with advanced material engineering can significantly improve the ...
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