Machine learning connects defect chemistry, defect physics and defect configurations with data-driven models to support the prediction and understanding of material defects. (IMAGE)

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Machine learning connects defect chemistry, defect physics and defect configurations with data-driven models to support the prediction and understanding of material defects.

Caption

Machine learning connects defect chemistry, defect physics and defect configurations with data-driven models to support the prediction and understanding of material defects.

Credit

Feifei Ren/Jilin University, Shijie Hu/Jilin University, Guanghui Zhang/Jilin University, Zenghua Cai/Suzhou University of Science and Technology, Dan Han/Jilin University

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