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Christopher J. Bartel

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Accelerating the prediction of inorganic surfaces with machine learning interatomic potentials

Dec 18, 2023
Kyle Noordhoek, Christopher J. Bartel

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CHGNet: Pretrained universal neural network potential for charge-informed atomistic modeling

Feb 28, 2023
Bowen Deng, Peichen Zhong, KyuJung Jun, Kevin Han, Christopher J. Bartel, Gerbrand Ceder

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Inorganic synthesis recommendation by machine learning materials similarity from scientific literature

Feb 05, 2023
Tanjin He, Haoyan Huo, Christopher J. Bartel, Zheren Wang, Kevin Cruse, Gerbrand Ceder

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A probabilistic deep learning approach to automate the interpretation of multi-phase diffraction spectra

Mar 30, 2021
Nathan J. Szymanski, Christopher J. Bartel, Yan Zeng, Qingsong Tu, Gerbrand Ceder

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