journal article·2023-10Open access

Ferroelastic twin domain patterns and polar domain walls of BiVO4 thin films via phase-field simulations

Ren-Ci Peng, Xiaoxing Cheng, Pao-Wen Shao, Fei Xue, Ying-Hao Chu, Long-Qing Chen, Yichun Zhou

Acta Materialia· Volume 259

Abstract

Polar domain walls in centrosymmetric ferroelastics (e.g., BiVO 4 films) give rise to inhomogeneity and offer promises for solar energy conversion applications via expediting charge-carrier separation. However, the origin of polar domain walls and the relationship between them and spontaneous strain from structural phase transition remain elusive at the mesoscale in BiVO 4 films. Here, from the perspective of phenomenological thermodynamics, the relationship between four variants of monoclinic (M) phase and the corresponding lattice parameters during the tetragonal-monoclinic (T-M) phase transition is revealed. Using phase-field simulations, it suggests that the formation of four variants of ferroelastic twin domains arises from spontaneous strain from T-M phase transition. Moreover, it is demonstrated that (i) polar domain walls in BiVO 4 films originate from the flexoelectric effect induced by strain gradient across the domain walls during phase transition process; (ii) shear strain gradient dominates the contribution to the polarization vectors at the domain walls; (iii) 180° head-to-head or tail-to-tail in-plane polarization configurations emerge at the adjacent domain walls. The stability of several types of ferroelastic domain walls is also analyzed from the point of view of total free energy. These results not only provide a fundamental understanding of the origin of polar domain walls and the formation mechanisms of ferroelastic twin patterns, but also stimulate potential applications of polar domain walls of non-polar BiVO 4 films in energy conversion.
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Research context

OpenAlex topics: Multiferroics and related materials · Ferroelectric and Piezoelectric Materials · Acoustic Wave Resonator Technologies

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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