Intrinsic structure of relaxor ferroelectrics from first principles
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| Main Authors: | , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866918408746958848 |
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| author | Xu, Xinyu Cai, Kehan Shi, Yubai Zhong, Peichen Xie, Pinchen |
| author_facet | Xu, Xinyu Cai, Kehan Shi, Yubai Zhong, Peichen Xie, Pinchen |
| contents | We develop FIRE-Swap, a first-principles framework for sampling intrinsic compositional structures in complex perovskites with machine-learning interatomic potentials (MLIPs). Using both dedicated and universal MLIPs, we study the relaxor lead magnesium niobate (PMN) and the solid solutions lead zirconate titanate (PZT) and lead strontium titanate (PST). Across MLIP models and exchange-correlation approximations, FIRE-Swap robustly predicts a rock-salt-like chemical order in PMN, which is absent in PZT and PST with the same mixing ratio, consistent with experiments. We further identify in PMN a distinct Nb-cluster morphology. Interconnected, non-coarsened polar nanoregions are found within Nb clusters, providing a mesoscale basis for understanding relaxor ferroelectricity. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2511_11097 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Intrinsic structure of relaxor ferroelectrics from first principles Xu, Xinyu Cai, Kehan Shi, Yubai Zhong, Peichen Xie, Pinchen Materials Science Disordered Systems and Neural Networks Mesoscale and Nanoscale Physics Statistical Mechanics We develop FIRE-Swap, a first-principles framework for sampling intrinsic compositional structures in complex perovskites with machine-learning interatomic potentials (MLIPs). Using both dedicated and universal MLIPs, we study the relaxor lead magnesium niobate (PMN) and the solid solutions lead zirconate titanate (PZT) and lead strontium titanate (PST). Across MLIP models and exchange-correlation approximations, FIRE-Swap robustly predicts a rock-salt-like chemical order in PMN, which is absent in PZT and PST with the same mixing ratio, consistent with experiments. We further identify in PMN a distinct Nb-cluster morphology. Interconnected, non-coarsened polar nanoregions are found within Nb clusters, providing a mesoscale basis for understanding relaxor ferroelectricity. |
| title | Intrinsic structure of relaxor ferroelectrics from first principles |
| topic | Materials Science Disordered Systems and Neural Networks Mesoscale and Nanoscale Physics Statistical Mechanics |
| url | https://arxiv.org/abs/2511.11097 |