Interface-controlled phase stability in polymorphic HfO2 revealed by machine-learning atomistic simulations

HfO 2 exhibits rich polymorphism, and competition among different phases underpins many of its functional properties. Yet bulk free-energy relations alone cannot explain phase selection at mixed-phase boundaries, where interface orientation and structural continuity constrain collective rearrangements. Here, using machine-learning atomistic simulations and a Hf-centered local phase classification scheme, we show that crystallographic interface matching redirects phase competition and accessible transformation pathways. The M(100)/T(100) interface remains pinned as an M/T mixture throughout 3 ns simulations from 300 to 1800 K. M/PO, M/AO, and PO/AO interfaces retain two-phase coexistence up to 900 K, whereas all T/PO interfaces become PO-dominant. At 1800 K, all non-M interfaces become T-dominant, while M-containing interfaces retain a monoclinic majority. Nudged elastic band calculations reveal lower-barrier routes through interface states. For M(100) → T(100), the interface-mediated route in a long cell (~12 nm) yields a barrier of 136.03 meV/f.u., 29.2% lower than the direct route in a short cell (~3 nm). This difference is associated with sequential phase-front motion absent from the short cell. These results identify phase boundaries as active participants in phase stability and transformation and establish interface orientation and crystallographic matching as variables for stabilizing metastable polymorphs and directing phase conversion in HfO 2 .

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Publication Details

Journal
npj Computational Materials
Published
2026-10-07
DOI
https://doi.org/10.1038/s41524-026-02353-x
Primary Topic
Ferroelectric and Negative Capacitance Devices
Type
article
Field-Weighted Citation Impact
0.00

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article

Interface-controlled phase stability in polymorphic HfO2 revealed by machine-learning atomistic simulations

Xudong Zhu, Lixin He, Junhong Li
npj Computational Materials
Ferroelectric and Negative Capacitance Devices
article

Interface-controlled phase stability in polymorphic HfO2 revealed by machine-learning atomistic simulations

Xudong Zhu, Lixin He, Junhong Li
article en

Abstract

HfO 2 exhibits rich polymorphism, and competition among different phases underpins many of its functional properties. Yet bulk free-energy relations alone cannot explain phase selection at mixed-phase boundaries, where interface orientation and structural continuity constrain collective rearrangements. Here, using machine-learning atomistic simulations and a Hf-centered local phase classification scheme, we show that crystallographic interface matching redirects phase competition and accessible transformation pathways. The M(100)/T(100) interface remains pinned as an M/T mixture throughout 3 ns simulations from 300 to 1800 K. M/PO, M/AO, and PO/AO interfaces retain two-phase coexistence up to 900 K, whereas all T/PO interfaces become PO-dominant. At 1800 K, all non-M interfaces become T-dominant, while M-containing interfaces retain a monoclinic majority. Nudged elastic band calculations reveal lower-barrier routes through interface states. For M(100) → T(100), the interface-mediated route in a long cell (~12 nm) yields a barrier of 136.03 meV/f.u., 29.2% lower than the direct route in a short cell (~3 nm). This difference is associated with sequential phase-front motion absent from the short cell. These results identify phase boundaries as active participants in phase stability and transformation and establish interface orientation and crystallographic matching as variables for stabilizing metastable polymorphs and directing phase conversion in HfO 2 .

npj Computational Materials
University of Science and Technology of China (CN)
University of Science and Technology of China, Anhui Provincial Department of Science and Technology
Openalex Percentile: Top 33%
Ferroelectric and Negative Capacitance Devices
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