Chalcogenide phase-change materials: unveiling new horizons with big data and machine learning
This review highlights how machine learning accelerates chalcogenide phase-change material research via high-throughput screening, large-scale simulations with machine learning potentials, and memory/neuromorphic device optimization.
Authors
- Kaiqi Li (ORCID: https://orcid.org/0000-0001-7862-4794)
- Jian Zhou (ORCID: https://orcid.org/0000-0003-0531-8918)
- Zhimei Sun (ORCID: https://orcid.org/0000-0002-4438-5032)
- Xuanguang Zhang
Institutions
- Beihang University (CN)
Publication Details
- Journal
- Journal of Materials Chemistry C
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1039/d5tc01074h
- Citations
- 5
- Primary Topic
- Phase-change materials and chalcogenides
- Type
- article
- Field-Weighted Citation Impact
- 2.59
Funders
- National Natural Science Foundation of China
- Beihang University