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Ideas: AI for materials discovery with Tian Xie and Ziheng Lu

Microsoft Research · published 16 January 2025

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https://www.microsoft.com/en-us/research/people/tianxie/?msockid=35739e94ab6c69d41b738b93aa076831
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https://www.microsoft.com/en-us/research/people/zihenglu/?msockid=35739e94ab6c69d41b738b93aa076831
microsoft.com
https://www.microsoft.com/en-us/research/blog/mattersim-a-deep-learning-model-for-materials-under-real-world-conditions/
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https://www.microsoft.com/en-us/research/publication/mattersim-a-deep-learning-atomistic-model-across-elements-temperatures-and-pressures/
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https://github.com/microsoft/mattersim
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https://www.nature.com/articles/s41586-025-08628-5
nature.com
https://www.microsoft.com/en-us/research/articles/mattergen-a-generative-model-for-materials-design/
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https://www.microsoft.com/en-us/research/blog/mattergen-property-guided-materials-design/
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https://github.com/microsoft/mattergen
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https://www.microsoft.com/en-us/research/publication/crystal-diffusion-variational-autoencoder-for-periodic-material-generation/
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https://www.microsoft.com/en-us/research/publication/crystal-graph-convolutional-neural-networks-for-an-accurate-and-interpretable-prediction-of-material-properties/
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