First-principles and machine-learning approaches for interpreting and predicting the properties of MXenes
Abstract MXenes are a versatile family of 2D inorganic materials with applications in energy storage, shielding, sensing, and catalysis. This review highlights computational studies using density functional theory and machine-learning approaches to explore their structure (stacking, functionalizatio...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-02-01
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| Series: | npj 2D Materials and Applications |
| Online Access: | https://doi.org/10.1038/s41699-025-00529-5 |
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