Scientists develop new machine learning method for modeling chemical reactions

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In this video: A simulation demonstrates the reactions that the ANI-1xnr can produce. ANI-1xnr can simulate reactive processes for organic materials, such as as carbon, using less computing power and time than traditional simulation models. The video is courtesy of Carnegie Mellon University's Shuhao Zhang, first author on "Exploring the Frontiers of Condensed-Phase Chemistry with a General Reactive Machine Learning Potential." Credit: Shuhao Zhang, Carnegie Mellon University

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