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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Predicting material failure: Machine learning spots early abnormal grain growth signs for safer designs
A team of Lehigh University researchers has successfully predicted abnormal grain growth in simulated polycrystalline materials for the first time—a development that could lead to the creation of ...
This Collection supports and amplifies research related to SDG 9: Industry & Innovation. The advent of architected materials, characterized by their unique structures and tailored mechanical ...
For most of the solar industry’s modern history, progress has been framed as a story of physics. Higher efficiencies came ...
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