Personal profile
Author IDs
ORCID iD: 0000-0002-2587-7883
Fingerprint
Dive into the research topics where Xin LI is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
- 1 Similar Profiles
Collaborations from the last five years
Recent external collaboration based on locations. Dive into details by clicking on the dots or
Research output
-
Machine learning studies for magnetic compositionally complex alloys: A critical review
Li, X., Shek, C.-H., Liaw, P. K. & Shan, G., Dec 2024, In: Progress in Materials Science. 146, 101332.Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
22 Link opens in a new tab Citations (Scopus) -
Domain knowledge aided machine learning method for properties prediction of soft magnetic metallic glasses
LI, X., SHAN, G.-C., Hong-bin ZHAO & SHEK, C. H., Jan 2023, In: Transactions of Nonferrous Metals Society of China. 33, 1, p. 209-219Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Open AccessFile27 Link opens in a new tab Citations (Scopus)44 Downloads (CityUHK Scholars) -
Efficient property-oriented optimization of magnetic high-entropy metallic glasses via a multi-stage design strategy
Li, X., Shan, G., Pang, S. & Shek, C.-H., Dec 2023, In: Applied Materials Today. 35, 101977.Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
5 Link opens in a new tab Citations (Scopus) -
Accelerated design for magnetic high entropy alloys using data-driven multi-objective optimization
Li, X., Shan, G., Zhang, J. & Shek, C.-H., 7 Dec 2022, In: Journal of Materials Chemistry C. 10, 45, p. 17291-17302Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
25 Link opens in a new tab Citations (Scopus) -
Bioinspired mineral MXene hydrogels for tensile strain sensing and radionuclide adsorption applications
Li, X., Shan, G., Ma, R., Shek, C.-H., Zhao, H. & Ramakrishna, S., Dec 2022, In: Frontiers of Physics. 17, 6, 63501.Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
19 Link opens in a new tab Citations (Scopus)
Thesis
-
Machine Learning Assisted Property Prediction and Optimization of Magnetic Compositionally Complex Alloys
LI, X. (Author), SHAN, G. (External Supervisor) & SHEK, C. H. (Supervisor), 16 May 2024Student thesis: Doctoral Thesis