Chi Chen

发表

Probing Solid–Solid Interfacial Reactions in All-Solid-State Sodium-Ion Batteries with First-Principles Calculations

Hanmei Tang, Z. Deng, Zhuonan Lin, 2018 .

Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals

Chi Chen, Chen Zheng, S. Ong, 2018, Chemistry of Materials.

A Critical Review of Machine Learning of Energy Materials

Z. Deng, Chi Chen, S. Ong, 2020, Advanced Energy Materials.

Learning properties of ordered and disordered materials from multi-fidelity data

Chi Chen, S. Ong, Yunxing Zuo, 2021, Nature Computational Science.

Multi-fidelity Graph Networks for Machine Learning the Experimental Properties of Ordered and Disordered Materials

Chi Chen, S. Ong, Yunxing Zuo, 2020, 2005.04338.

A Performance and Cost Assessment of Machine Learning Interatomic Potentials.

J. Behler, Z. Deng, Chi Chen, 2019, The journal of physical chemistry. A.

An electrostatic spectral neighbor analysis potential for lithium nitride

Z. Deng, Chi Chen, S. Ong, 2019, npj Computational Materials.

An electrostatic spectral neighbor analysis potential for lithium nitride

Shyue Ping Ong, Zhi Deng, Z. Deng, 2019, npj Computational Materials.

Unravelling Complex Strengthening Mechanisms in the NbMoTaW Multi-Principal Element Alloy with Machine Learning Potentials

Chi Chen, S. Ong, Xiang-Guo Li, 2019 .

Quantum-accurate spectral neighbor analysis potential models for Ni-Mo binary alloys and fcc metals

Jian Luo, Shyue Ping Ong, Zhi Deng, 2018, Physical Review B.

Accurate Force Field for Molybdenum by Machine Learning Large Materials Data

Shyue Ping Ong, Hanmei Tang, Iek-Heng Chu, 2017, 1706.09122.

Random Forest Models for Accurate Identification of Coordination Environments from X-Ray Absorption Near-Edge Structure

Chi Chen, Chen Zheng, S. Ong, 2019, Patterns.

Automated generation and ensemble-learned matching of X-ray absorption spectra

Hanmei Tang, Chi Chen, Chen Zheng, 2017, npj Computational Materials.

High-throughput computational X-ray absorption spectroscopy

Chi Chen, Chen Zheng, S. Ong, 2018, Scientific Data.

Deep neural networks for accurate predictions of crystal stability

Shyue Ping Ong, Iek-Heng Chu, Weike Ye, 2017, Nature Communications.

Predicting Thermal Quenching in Inorganic Phosphors

Hanmei Tang, Zhenbin Wang, Chi Chen, 2020 .

A Universal Machine Learning Model for Elemental Grain Boundary Energies

Chi Chen, S. Ong, Weike Ye, 2022, SSRN Electronic Journal.

Grain boundary properties of elemental metals

Chi Chen, S. Ong, K. Persson, 2019, Acta Materialia.

Genetic algorithm-guided deep learning of grain boundary diagrams: Addressing the challenge of five degrees of freedom

Chi Chen, Yunxing Zuo, Chongze Hu, 2020, 2002.10632.

A universal graph deep learning interatomic potential for the periodic table

Chi Chen, S. Ong, 2022, Nature Computational Science.

Thermodynamics and Kinetics of the Cathode–Electrolyte Interface in All-Solid-State Li–S Batteries

Chi Chen, S. Ong, Swastika Banerjee, 2022, Journal of the American Chemical Society.

Intercalation Chemistry of the Disordered Rocksalt Li3V2O5 Anode from Cluster Expansions and Machine Learning Interatomic Potentials

Chi Chen, S. Ong, Xingyu Guo, 2022, Chemistry of Materials.

Multi-scale Investigation of Chemical Short-Range Order and Dislocation Glide in the MoNbTi and TaNbTi Refractory Multi-Principal Element Alloys

Chi Chen, S. Ong, Xiang-Guo Li, 2022 .

All‐Electric Nonassociative Learning in Nickel Oxide

Chi Chen, S. Ong, K. Roy, 2022, Adv. Intell. Syst..

Electrochemically induced amorphous-to-rock-salt phase transformation in niobium oxide electrode for Li-ion batteries

Chi Chen, Zhuoying Zhu, S. Ong, 2022, Nature Materials.

Efficient near-infrared phosphors discovered by parametrizing the Eu(II) 5d-to-4f energy gap

Zhenbin Wang, Chi Chen, S. Ong, 2022, Matter.

Recent advances and applications of deep learning methods in materials science

Brian L. DeCost, Cheol Woo Park, A. Choudhary, 2021, npj Computational Materials.

Data Descriptor: High-throughput computational X-ray absorption spectroscopy

Kristin A. Persson, Chi Chen, Chen Zheng, 2018 .

Complex strengthening mechanisms in the NbMoTaW multi-principal element alloy

Chi Chen, S. Ong, Yunxing Zuo, 2019, npj Computational Materials.

Deep neural networks for accurate predictions of crystal stability

Zhenbin Wang, Iek-Heng Chu, Chi Chen, 2017, Nature Communications.

Accelerating materials discovery with Bayesian optimization and graph deep learning

Chi Chen, S. Ong, Yunxing Zuo, 2021, Materials Today.

AtomSets as a hierarchical transfer learning framework for small and large materials datasets

Chi Chen, S. Ong, 2021, npj Computational Materials.

Harnessing the Materials Project for machine-learning and accelerated discovery

Anubhav Jain, Kristin A. Persson, Shyue Ping Ong, 2018, MRS Bulletin.

Multiprincipal Component P2-Na0.6(Ti0.2Mn0.2Co0.2Ni0.2Ru0.2)O2 as a High-Rate Cathode for Sodium-Ion Batteries

Chi Chen, Chen Zheng, S. Ong, 2020, JACS Au.

Multi-fidelity Graph Networks for Deep Learning the Experimental Properties of Ordered and Disordered Materials

Chi Chen, S. Ong, Yunxing Zuo, 2020 .

Bridging the gap between simulated and experimental ionic conductivities in lithium superionic conductors

Chi Chen, Zhuoying Zhu, S. Ong, 2021, 2102.08413.

Author Correction: Automated generation and ensemble-learned matching of X-ray absorption spectra

Hanmei Tang, Chi Chen, Chen Zheng, 2018, npj Computational Materials.

Database of ab initio L-edge X-ray absorption near edge structure

Chi Chen, Chen Zheng, S. Ong, 2021, Scientific data.

Polaron-induced metal-to-insulator transition in vanadium oxides from density functional theory calculations

Chi Chen, S. Ong, J. Kaur, 2023, Physical Review B.

Unified Theory of Thermal Quenching in Inorganic Phosphors

Hanmei Tang, Zhenbin Wang, Chi Chen, 2019, 1910.12420.

Lawrence Berkeley National Laboratory Recent Work Title A Performance and Cost Assessment of Machine Learning Interatomic Potentials Permalink

Z. Deng, Chi Chen, S. Ong, 2019 .

A Performance and Cost Assessment of Machine Learning Interatomic Potentials.

J. Behler, Z. Deng, Chi Chen, 2019, The journal of physical chemistry. A.

Learning properties of ordered and disordered materials from multi-fidelity data

Chi Chen, S. Ong, Yunxing Zuo, 2021, Nature Computational Science.

Multi-scale investigation of short-range order and dislocation glide in MoNbTi and TaNbTi multi-principal element alloys

Chi Chen, S. Ong, Xiang-Guo Li, 2022, 2203.03767.