| A physics-informed machine learning model for porosity analysis in laser powder bed fusion additive manufacturing R Liu, S Liu, X Zhang The International Journal of Advanced Manufacturing Technology 113 (7), 1943 …, 2021 | 104 | 2021 |
| Physics-informed machine learning for composition –process –property design: Shape memory alloy demonstration S Liu, BB Kappes, B Amin-ahmadi, O Benafan, X Zhang, AP Stebner Applied Materials Today 22, doi.org/10.1016/j.apmt.2020.100898, 2020 | 94 | 2020 |
| Machine learning for knowledge transfer across multiple metals additive manufacturing printers S Liu, AP Stebner, BB Kappes, X Zhang Additive Manufacturing 39, 101877, 2021 | 70 | 2021 |
| In-process comprehensive prediction of bead geometry for laser wire-feed DED system using molten pool sensing data and multi-modality CNN ND Jamnikar, S Liu, C Brice, X Zhang The International Journal of Advanced Manufacturing Technology 121 (1), 903-917, 2022 | 22 | 2022 |
| In situ microstructure property prediction by modeling molten pool-quality relations for wire-feed laser additive manufacturing ND Jamnikar, S Liu, C Brice, X Zhang Journal of Manufacturing Processes 79, 803-814, 2022 | 15 | 2022 |
| Simulation of particle trajectory in the head–disk interface S Liu, H Li, S Shen, S Wu IEEE Transactions on Magnetics 51 (11), 1-4, 2015 | 11 | 2015 |
| Interrelated process-geometry-microstructure relationships for wire-feed laser additive manufacturing S Liu, C Brice, X Zhang Materials Today Communications 31, 103794, 2022 | 10 | 2022 |
| Simulation of particle rebounding from the slider air bearing surface S Liu, H Li, S Shen, S Wu Microsystem Technologies 22, 1475-1481, 2016 | 8 | 2016 |
| Hierarchical bead materials multi-property design for wire-feed laser additive manufacturing S Liu, C Brice, X Zhang Journal of Manufacturing Processes 80, 546-557, 2022 | 7 | 2022 |
| A physics-informed feature engineering approach to use machine learning with limited amounts of data for alloy design: shape memory alloy demonstration S Liu, BB Kappes, B Amin-ahmadi, O Benafan, AP Stebner, X Zhang CoRR, 1-32, 2020 | 6 | 2020 |
| Simulation of air flow and particle trajectories in the head–disk interface F Cui, H Li, S Shen, S Liu, S Wu IEEE Transactions on Magnetics 52 (12), 1-5, 2016 | 5 | 2016 |
| Localized keyhole pore prediction during laser powder bed fusion via multimodal process monitoring and X-ray radiography S Gorgannejad, AA Martin, JW Nicolino, M Strantza, GM Guss, ... Additive Manufacturing 78, 103810, 2023 | 4 | 2023 |
| Comprehensive molten pool condition-process relations modeling using CNN for wire-feed laser additive manufacturing N Jamnikar, S Liu, C Brice, X Zhang Journal of Manufacturing Processes 98, 42-53, 2023 | 4 | 2023 |
| Automated phase segmentation and quantification of high-resolution TEM image for alloy design S Liu, B Amin-Ahmadi, R Liu, Q Zheng, X Zhang Materials Characterization 199, 112779, 2023 | 4 | 2023 |
| Comprehensive Quality Investigations of Wirefeed Additive Manufacturing based on Machine Learning of Experimental Data S Liu, C Brice, X Zhang arXiv preprint arXiv 2103, 2021 | 4 | 2021 |
| Physics-informed machine learning for composition-process-property alloy design: shape memory alloy demonstration S Liu, BB Kappes, B Amin-ahmadi, O Benafan, X Zhang, AP Stebner arXiv preprint arXiv:2003.01878, 2020 | 4 | 2020 |
| Modeling of formation and breaking of lubricant bridge in the head–disk interface by molecular dynamic simulation X Dai, H Li, X Lei, S Shen, S Wu, S Liu, H Du Molecular Simulation 44 (2), 94-99, 2018 | 4 | 2018 |
| Simulations of particle trajectories in hard disk drives considering the trapping criterion G Zhang, Y Zhu, H Li, S Shen, Y Yang, S Liu, X Lei, S Wu IEEE Transactions on Magnetics 52 (8), 1-6, 2016 | 4 | 2016 |
| Comprehensive process-molten pool relations modeling using CNN for wire-feed laser additive manufacturing N Jamnikar, S Liu, C Brice, X Zhang arXiv preprint arXiv:2103.11588, 2021 | 3 | 2021 |
| Machine learning based in situ quality estimation by molten pool condition-quality relations modeling using experimental data N Jamnikar, S Liu, C Brice, X Zhang arXiv preprint arXiv:2103.12066, 2021 | 3 | 2021 |
Dr. Xiaoli ZhangAssociate Professor, Colorado School of Mines在 mines.edu 的电子邮件经过验证
