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Two-dimensional hybrid organic–inorganic perovskites as emergent ferroelectric materials

Summary

Hybrid organic–inorganic perovskites (HOIPs) have attracted intense interest for photovoltaics and light-emitting devices because their compositions and dimensionalities tune electronic structure in useful ways. This Journal of Applied Physics perspective extends that materials story to ferroelectric behavior in two-dimensional HOIPs (2D HOIPs), treating them as an emerging class of room-temperature-processable polar materials that can complement classical oxide ferroelectrics such as barium titanate and lead titanate. The article connects molecular-scale structure—organic cation ordering, inorganic framework distortions, and layer stacking—to macroscopic polarization concepts and figures of merit relevant to ferroelectric switching and device engineering. It also discusses how atomistic modeling and machine-learning-assisted potentials can accelerate screening of compositions and heterostructures, positioning computation as a partner to experiment in materials-by-design for 2D HOIP ferroelectrics rather than as a single fixed simulation benchmark.

Methods

The publication is a perspective article: it synthesizes literature on ferroelectric mechanisms in HOIPs (including order–disorder versus displacive motifs, layer-dependent polarization, and practical processing constraints) and outlines conceptual workflows for atomistic and machine-learning methods applied to new 2D HOIP candidates. It is not centered on one proprietary molecular dynamics protocol, one training set, or one experimental growth run; instead, it cites representative studies across synthesis, characterization, and modeling communities. Readers seeking a single “Methods” block for reproduction should follow references within the perspective to primary experimental and computational papers.

Findings

The perspective argues that 2D HOIPs can exhibit ferroelectric responses tied to structural sources of polar order that differ from bulk oxide perovskites, and that their processability at comparatively mild conditions offers a complementary design space to high-temperature ceramic ferroelectrics. It emphasizes how chemisorption, layer stacking, and heterostructure engineering influence polarization stability and switching pathways, and it frames open challenges around fatigue, retention, and interface chemistry that matter for realistic devices. Quantitative predictions in the article are attributed to cited primary sources rather than generated de novo in the perspective itself. Machine-learning and atomistic workflows discussed in the article are positioned as accelerators for screening new compositions rather than as single closed-form benchmarks.

Limitations

As a review-style piece, it prioritizes breadth; barrier heights, coercive fields, and growth windows for specific chemistries must be taken from the underlying studies. Coarse-grained or ML potentials mentioned are illustrative and require validation per application.

Relevance to group

Adri van Duin is a co-author; the note links perovskite ferroelectric interest to computational materials themes elsewhere in the wiki.

Citations and evidence anchors