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AI and Cloud Computing Revolutionize Materials Discovery, Predict Half a Million Stable Materials in 80 Hours

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Researchers from Azure Quantum Microsoft, Physical and Computational Sciences Directorate Pacific Northwest National Laboratory, and Microsoft Surface have successfully integrated artificial intelligence (AI) models and cloud high-performance computing (HPC) to expedite the discovery of new materials. The team used this approach to sift through over 32 million candidates and predict approximately half a million potentially stable materials in under 80 hours. The research focused on solid-state electrolytes for battery applications, identifying 18 promising candidates with new compositions. This method could revolutionize materials discovery, reducing the time from concept to solution.

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