arXiv · 2511.11097
Intrinsic structure of relaxor ferroelectrics from first principles
Abstract
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.
Explore related subjects
Keep this discovery
Xinyu Xu, Kehan Cai, Yubai Shi, Peichen Zhong, Pinchen Xie. 2025-11-14. Intrinsic structure of relaxor ferroelectrics from first principles. https://doi.org/10.1103/fz5h-1t5b
Cite the original work for its findings. Save a collection to share your selection of sources.