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Machine learning and evolutionary prediction of superhard B-C-N compounds

Physics

Machine learning and evolutionary prediction of superhard B-C-N compounds

W. Chen, J. N. Schmidt, et al.

This groundbreaking research, conducted by Wei-Chih Chen, Joanna N. Schmidt, Da Yan, Yogesh K. Vohra, and Cheng-Chien Chen, showcases the power of random forests models to predict superhard materials from chemical formulas. The study reveals that a 1:1 B-N ratio can lead to several dynamically stable superhard compounds, pushing the boundaries of materials science through innovative machine learning techniques.

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