| Prediction of MXene based 2D tunable band gap semiconductors: GW quasiparticle calculations Y Zhang, W Xia, Y Wu, P Zhang Nanoscale 11 (9), 3993-4000, 2019 | 84 | 2019 |
| Speeding up GW calculations to meet the challenge of large scale quasiparticle predictions W Gao, W Xia, X Gao, P Zhang Scientific reports 6 (1), 36849, 2016 | 75 | 2016 |
| Quasiparticle band structures of CuCl, CuBr, AgCl, and AgBr: The extreme case W Gao, W Xia, Y Wu, W Ren, X Gao, P Zhang Physical Review B 98 (4), 045108, 2018 | 42 | 2018 |
| Semimetal or Semiconductor: The Nature of High Intrinsic Electrical Conductivity in TiS2 H Wang, Z Qiu, W Xia, C Ming, Y Han, L Cao, J Lu, P Zhang, S Zhang, ... The journal of physical chemistry letters 10 (22), 6996-7001, 2019 | 41 | 2019 |
| Engineering the near-edge electronic structure of SnSe through strains Y Wu, W Xia, W Gao, W Ren, P Zhang Physical Review Applied 8 (3), 034007, 2017 | 27 | 2017 |
| Prediction of protected band edge states and dielectric tunable quasiparticle and excitonic properties of monolayer MoSi2N4 Y Wu, Z Tang, W Xia, W Gao, F Jia, Y Zhang, W Zhu, W Zhang, P Zhang npj Computational Materials 8 (1), 129, 2022 | 25 | 2022 |
| Quasiparticle electronic structure of honeycomb C3N: from monolayer to bulk Y Wu, W Xia, W Gao, F Jia, P Zhang, W Ren 2D Materials 6 (1), 015018, 2018 | 25 | 2018 |
| Giant Narrow-Band Optical Absorption and Distinctive Excitonic Structures of Monolayer and Z Tang, GJ Cruz, Y Wu, W Xia, F Jia, W Zhang, P Zhang Physical Review Applied 17 (3), 034068, 2022 | 16 | 2022 |
| Accelerating the discovery of novel magnetic materials using machine learning–guided adaptive feedback W Xia, M Sakurai, B Balasubramanian, T Liao, R Wang, C Zhang, H Sun, ... Proceedings of the National Academy of Sciences 119 (47), e2204485119, 2022 | 12 | 2022 |
| Combined subsampling and analytical integration for efficient large-scale GW calculations for 2D systems W Xia, W Gao, G Lopez-Candales, Y Wu, W Ren, W Zhang, P Zhang npj Computational Materials 6 (1), 118, 2020 | 12 | 2020 |
| Remarkable Band-Gap Renormalization via Dimensionality of the Layered Material Y Wu, W Xia, Y Zhang, W Zhu, W Zhang, P Zhang Physical Review Applied 14 (1), 014073, 2020 | 11 | 2020 |
| Quasiparticle band structure of and : A combined and approach G Lopez-Candales, Z Tang, W Xia, F Jia, P Zhang Physical Review B 103 (3), 035128, 2021 | 9 | 2021 |
| Magnetic iron-cobalt silicides discovered using machine-learning T Liao, W Xia, M Sakurai, R Wang, C Zhang, H Sun, KM Ho, CZ Wang, ... Physical Review Materials 7 (3), 034410, 2023 | 8 | 2023 |
| Machine learning guided discovery of ternary compounds involving La and immiscible Co and Pb elements R Wang, W Xia, TJ Slade, X Fan, H Dong, KM Ho, PC Canfield, CZ Wang npj Computational Materials 8 (1), 258, 2022 | 6 | 2022 |
| Predicting magnetic anisotropy energies using site-specific spin-orbit coupling energies and machine learning: Application to iron-cobalt nitrides T Liao, W Xia, M Sakurai, R Wang, C Zhang, H Sun, KM Ho, CZ Wang, ... Physical Review Materials 6 (2), 024402, 2022 | 6 | 2022 |
| Ab initio study of thermodynamically consistent equation of state of warm dense aluminum plasma X Gao, L Chen, R Valencia, W Xia, W Gao, XY Han, JM Li, P Zhang Physics of Plasmas 23 (9), 2016 | 6 | 2016 |
| Machine learning-guided discovery of ternary compounds containing La, P, and group 14 elements H Sun, C Zhang, W Xia, L Tang, R Wang, G Akopov, NW Hewage, KM Ho, ... Inorganic Chemistry 61 (42), 16699-16706, 2022 | 5 | 2022 |
| How to Look for Compounds: Predictive Screening and in situ Studies in Na− Zn− Bi System V Gvozdetskyi, R Wang, W Xia, F Zhang, Z Lin, KM Ho, G Miller, ... Chemistry–A European Journal 27 (64), 15954-15966, 2021 | 4 | 2021 |
| MoSi2N4: an emerging 2D electronic material with protected band edge states and dielectric tunable quasiparticle and optical properties Y Wu, Z Tang, W Xia, W Gao, F Jia, Y Zhang, W Zhu, W Zhang, P Zhang arXiv preprint arXiv:2107.10126, 2021 | 4 | 2021 |
| Molecular dynamics simulation of Fe-Si alloys using a neural network machine learning potential H Sun, C Zhang, L Tang, R Wang, W Xia, CZ Wang Physical Review B 107 (22), 224301, 2023 | 3 | 2023 |
