检索结果 - Duan, Chenru

New Strategies for Direct Methane-to-Methanol Conversion from Active Learning Exploration of 16 Million Catalysts 由 Nandy, Aditya, Duan, Chenru, Goffinet, Conrad, Kulik, Heather J.

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Accurate Multiobjective Design in a Space of Millions of Transition Metal Complexes with Neural-Network-Driven Efficient Global Optimization 由 Janet, Jon Paul, Ramesh, Sahasrajit, Duan, Chenru, Kulik, Heather J.

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Detection of multi-reference character imbalances enables a transfer learning approach for virtual high throughput screening with coupled cluster accuracy at DFT cost 由 Duan, Chenru, Chu, Daniel B. K., Nandy, Aditya, Kulik, Heather J.

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A quantitative uncertainty metric controls error in neural network-driven chemical discovery 由 Janet, Jon Paul, Duan, Chenru, Yang, Tzuhsiung, Nandy, Aditya, Kulik, Heather J.

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Machine learning to tame divergent density functional approximations: a new path to consensus materials design principles 由 Duan, Chenru, Chen, Shuxin, Taylor, Michael G., Liu, Fang, Kulik, Heather J.

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MOFSimplify, machine learning models with extracted stability data of three thousand metal–organic frameworks 由 Nandy, Aditya, Terrones, Gianmarco, Arunachalam, Naveen, Duan, Chenru, Kastner, David W., Kulik, Heather J.

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Seeing Is Believing: Experimental Spin States from Machine Learning Model Structure Predictions 由 Taylor, Michael G., Yang, Tzuhsiung, Lin, Sean, Nandy, Aditya, Janet, Jon Paul, Duan, Chenru, Kulik, Heather J.

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