Influence of the Discretization Methods on the Distribution of Relaxation Times Deconvolution: Implementing Radial Basis Functions with DRTtools TH Wan, M Saccoccio, C Chen, F Ciucci Electrochimica Acta 184, 483-499, 2015 | 1294 | 2015 |
Graph networks as a universal machine learning framework for molecules and crystals C Chen, W Ye, Y Zuo, C Zheng, SP Ong Chemistry of Materials 31 (9), 3564-3572, 2019 | 1078 | 2019 |
Nonstoichiometric Oxides as Low-Cost and Highly-Efficient Oxygen Reduction/Evolution Catalysts for Low-Temperature Electrochemical Devices D Chen†, C Chen†, ZM Baiyee, Z Shao, F Ciucci Chemical Reviews 115 (18), 9869-9921, 2015 | 892 | 2015 |
Performance and Cost Assessment of Machine Learning Interatomic Potentials Y Zuo, C Chen, X Li, Z Deng, Y Chen, J Behler, G Csányi, AV Shapeev, ... The Journal of Physical Chemistry A 124 (4), 731-745, 2020 | 667 | 2020 |
A critical review of machine learning of energy materials C Chen*, Y Zuo, W Ye, X Li, Z Deng, SP Ong* Advanced Energy Materials 10 (8), 1903242, 2020 | 462 | 2020 |
Recent advances and applications of deep learning methods in materials science K Choudhary, B DeCost, C Chen, A Jain, F Tavazza, R Cohn, CW Park, ... npj Computational Materials 8 (1), 1-26, 2022 | 449 | 2022 |
Analysis of Electrochemical Impedance Spectroscopy Data Using the Distribution of Relaxation Times: A Bayesian and Hierarchical Bayesian Approach F Ciucci, C Chen Electrochimica Acta 167, 439-454, 2015 | 399 | 2015 |
A universal graph deep learning interatomic potential for the periodic table C Chen*, SP Ong* Nature Computational Science 2 (11), 718-728, 2022 | 349 | 2022 |
Optimal Regularization in Distribution of Relaxation Times applied to Electrochemical Impedance Spectroscopy: Ridge and Lasso Regression Methods-A Theoretical and Experimental … M Saccoccio, TH Wan, C Chen, F Ciucci Electrochimica Acta 147, 470-482, 2014 | 304 | 2014 |
Deep neural networks for accurate predictions of crystal stability W Ye, C Chen, Z Wang, IH Chu, SP Ong Nature Communications 9 (1), 3800, 2018 | 267 | 2018 |
Complex strengthening mechanisms in the NbMoTaW multi-principal element alloy XG Li, C Chen, H Zheng, Y Zuo, SP Ong npj Computational Materials 6 (1), 70, 2020 | 202 | 2020 |
Probing solid–solid interfacial reactions in all-solid-state sodium-ion batteries with first-principles calculations H Tang, Z Deng, Z Lin, Z Wang, IH Chu, C Chen, Z Zhu, C Zheng, SP Ong Chemistry of Materials 30 (1), 163-173, 2018 | 177 | 2018 |
Theoretical and experimental investigation on a thermoelectric cooling and heating system driven by solar W He, J Zhou, J Hou, C Chen, J Ji Applied Energy 107, 89-97, 2013 | 175 | 2013 |
Grain boundary properties of elemental metals H Zheng, XG Li, R Tran, C Chen, M Horton, D Winston, KA Persson, ... Acta Materialia 186, 40-49, 2020 | 173 | 2020 |
Accurate force field for molybdenum by machine learning large materials data C Chen, Z Deng, R Tran, H Tang, IH Chu, SP Ong Physical Review Materials 1 (4), 043603, 2017 | 155 | 2017 |
Learning properties of ordered and disordered materials from multi-fidelity data C Chen, Y Zuo, W Ye, X Li, SP Ong Nature Computational Science 1 (1), 46-53, 2021 | 151 | 2021 |
Defect chemistry and lithium transport in Li3OCl anti-perovskite superionic conductors Z Lu, C Chen, ZM Baiyee, X Chen, C Niu, F Ciucci Physical Chemistry Chemical Physics 17 (48), 32547-32555, 2015 | 144 | 2015 |
Automated generation and ensemble-learned matching of X-ray absorption spectra C Zheng†, K Mathew†, C Chen†, Y Chen, H Tang, A Dozier, JJ Kas, ... npj Computational Materials 4 (1), 12, 2018 | 137 | 2018 |
The effect of A-site and B-site substitution on BaFeO3−δ: An investigation as a cathode material for intermediate-temperature solid oxide fuel cells J Wang, M Saccoccio, D Chen, Y Gao, C Chen, F Ciucci Journal of Power Sources 297, 511-518, 2015 | 137 | 2015 |
High-throughput computational X-ray absorption spectroscopy K Mathew, C Zheng, D Winston, C Chen, A Dozier, JJ Rehr, SP Ong, ... Scientific data 5 (1), 1-8, 2018 | 128 | 2018 |