Two computational methods — one physics-based, and the other one deep-learning based — are proposed to enable the systematic investigation of magnetic order in moiré magnets from first principles.
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panel c adapted from ref. 2, Springer Nature America Inc
References
Yang, B., Li, Y., Xiang, H., Lin, H. & Huang, B. Nat. Comput. Sci. https://doi.org/10.1038/s43588-023-00430-5 (2023).
Li, H. et al. Nat. Comput. Sci. https://doi.org/10.1038/s43588-023-00424-3 (2023).
Cao, Y. et al. Nature 556, 43–50 (2018).
Huang, B. et al. Nature 546, 270–273 (2017).
Sivadas, N. et al. Nano Lett. 18, 7658–7664 (2018).
Akram, M. et al. Nano Lett. 21, 6633–6639 (2021).
Fert, A., Cros, V. & Sampaio, J. Nat. Nanotechnol. 8, 152–156 (2013).
Jiang, W. et al. Science 349, 283–286 (2015).
Zheng, F. Adv. Funct. Mater. 33, 2206923 (2023).
Edström, A. et al. Phys. Rev. Lett. 128, 177202 (2022).
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Soriano, D. Uncovering magnetic interactions in moiré magnets. Nat Comput Sci 3, 282–284 (2023). https://doi.org/10.1038/s43588-023-00434-1
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DOI: https://doi.org/10.1038/s43588-023-00434-1
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