| A machine-learning approach to predicting and understanding the properties of amorphous metallic alloys J Xiong, SQ Shi, TY Zhang Materials & design 187, 108378, 2020 | 181 | 2020 |
| Machine Learning of Mechanical Properties of Steels J Xiong, TY Zhang, SQ Shi SCIENCE CHINA Technological Sciences, 2020 | 91 | 2020 |
| Machine learning of phases and mechanical properties in complex concentrated alloys J Xiong, SQ Shi, TY Zhang Journal of Materials Science & Technology 87, 133-142, 2021 | 79 | 2021 |
| Machine learning prediction of elastic properties and glass-forming ability of bulk metallic glasses J Xiong, TY Zhang, SQ Shi MRS Communications, 1-10, 2019 | 72 | 2019 |
| Identifying facile material descriptors for Charpy impact toughness in low-alloy steel via machine learning Y Chen, S Wang, J Xiong, G Wu, J Gao, Y Wu, G Ma, HH Wu, X Mao Journal of Materials Science & Technology 132, 213-222, 2023 | 33 | 2023 |
| Machine learning prediction of glass-forming ability in bulk metallic glasses J Xiong, SQ Shi, TY Zhang Computational Materials Science 192, 110362, 2021 | 29 | 2021 |
| Data-driven glass-forming ability criterion for bulk amorphous metals with data augmentation J Xiong, TY Zhang Journal of Materials Science & Technology 121, 99-104, 2022 | 24 | 2022 |
| Deep learning-assisted elastic isotropy identification for architected materials A Wei, J Xiong, W Yang, F Guo Extreme Mechanics Letters 43, 101173, 2021 | 18 | 2021 |
| Gaussian process regressions on hot deformation behaviors of FGH98 nickel-based powder superalloy J Xiong, JC He, XS Leng, TY Zhang Journal of Materials Science & Technology 146, 177-185, 2023 | 11 | 2023 |
| Pinning behavior of glycine-doped MgB2 bulks with excellent critical current density by Cu-activated low-temperature sintering Q Cai, Y Liu, Z Ma, L Yu, J Xiong, H Li Journal of alloys and compounds 585, 78-84, 2014 | 11 | 2014 |
| SISSO-assisted prediction and design of mechanical properties of porous graphene with a uniform nanopore array A Wei, H Ye, Z Guo, J Xiong Nanoscale Advances 4 (5), 1455-1463, 2022 | 6 | 2022 |
| Identifying intrinsic factors for ductile-to-brittle transition temperatures in Fe–Al intermetallics via machine learning D Zhu, K Pan, HH Wu, Y Wu, J Xiong, XS Yang, Y Ren, H Yu, S Wei, ... Journal of Materials Research and Technology 26, 8836-8845, 2023 | 4 | 2023 |
| Data driven discovery of an analytic formula for the life prediction of Lithium-ion batteries J Xiong, TX Lei, DM Fu, JW Wu, TY Zhang Progress in Natural Science: Materials International 32 (6), 793-799, 2022 | 4 | 2022 |
| Evaluation of quenching-induced lattice strain and superconducting properties in un-doped and glycine-doped MgB2 bulks Q Cai, Z Ma, Y Liu, Q Guo, J Xiong, H Li, F Qin Journal of Materials Science: Materials in Electronics 27, 9431-9436, 2016 | 4 | 2016 |
| Enhancement of Critical Current Density in MgB2 Bulk with CNT-coated Al Addition J Xiong, Q Cai, Z Ma, L Yu, Y Liu Journal of Superconductivity and Novel Magnetism 27, 1659-1664, 2014 | 4 | 2014 |
| Enhancement of critical current density in MgB2 bulks burying sintered with commercial MgB2 powder Q Cai, Y Liu, J Xiong, Z Ma Journal of Materials Science: Materials in Electronics 29, 10323-10328, 2018 | 3 | 2018 |
| Application of Constitutive Models and Machine Learning Models to Predict the Elevated Temperature Flow Behavior of TiAl Alloy R Zhao, J He, H Tian, Y Jing, J Xiong Materials 16 (14), 4987, 2023 | 1 | 2023 |
| MLMD: a programming-free AI platform to predict and design materials J Ma, B Cao, S Dong, Y Tian, M Wang, J Xiong, S Sun npj Computational Materials 10 (1), 59, 2024 | | 2024 |
San-Qiang ShiChair Professor and Head of Mechanical Engineering (2010-2011, 2014-2021), Hong Kong PolytechnicVerified email at connect.polyu.hk
