Process-structure linkages using a data science approach: application to simulated additive manufacturing data E Popova, TM Rodgers, X Gong, A Cecen, JD Madison, SR Kalidindi Integrating materials and manufacturing innovation 6, 54-68, 2017 | 143 | 2017 |
High throughput assays for additively manufactured Ti-Ni alloys based on compositional gradients and spherical indentation X Gong, S Mohan, M Mendoza, A Gray, P Collins, SR Kalidindi Integrating Materials and Manufacturing Innovation 6, 218-228, 2017 | 21 | 2017 |
Evaluation of Ti–Mn alloys for additive manufacturing using high-throughput experimental assays and gaussian process regression X Gong, YC Yabansu, PC Collins, SR Kalidindi Materials 13 (20), 4641, 2020 | 18 | 2020 |
Process-structure linkages using a data science approach: application to simulated additive manufacturing data. Integr Mater Manuf Innov 6: 54–68 E Popova, TM Rodgers, X Gong, A Cecen, JD Madison, SR Kalidindi | 17* | 2017 |
High throughput assays for exploring materials space for additive manufacturing X Gong Georgia Institute of Technology, 2019 | | 2019 |
Dynamical Networks for Smog Pattern Analysis L Zong, X Gong, J Zhu arXiv preprint arXiv:1511.06869, 2015 | | 2015 |