Ultrahigh Oxygen Ion Mobility in Ferroelectric Hafnia

Physical Review Letters, Journal Year: 2023, Volume and Issue: 131(25)

Published: Dec. 20, 2023

Ferroelectrics and ionic conductors are important functional materials, each supporting a plethora of applications in information energy technology. The underlying physics governing their properties is motion, yet studies ferroelectrics often considered separate fields. Based on first-principles calculations deep-learning-assisted large-scale molecular dynamics simulations, we report ferroelectric-switching-promoted oxygen ion transport ${\mathrm{HfO}}_{2}$, wide-band-gap insulator with both ferroelectricity conductivity. Applying unidirectional bias can activate multiple switching pathways ferroelectric leading to polar-antipolar phase cycling that appears contradict classical electrodynamics. This apparent conflict resolved by the geometric-quantum-phase nature electric polarization carries no definite direction. Our simulations demonstrate bias-driven successive transitions facilitate ultrahigh mobility at moderate temperatures, highlighting potential combining conductivity for development advanced materials technologies.

Language: Английский

---

Giant Piezoelectric Effects of Topological Structures in Stretched Ferroelectric Membranes

Physical Review Letters, Journal Year: 2024, Volume and Issue: 133(4)

Published: July 26, 2024

Freestanding ferroelectric oxide membranes emerge as a promising platform for exploring the interplay between topological polar ordering and dipolar interactions that are continuously tunable by strain. Our investigations combining density functional theory (DFT) deep-learning-assisted molecular dynamics simulations demonstrate DFT-predicted strain-driven morphotropic phase boundary involving monoclinic phases manifest diverse domain structures at room temperatures, featuring continuous distributions of dipole orientations mobile walls. Detailed analysis dynamic reveals enhanced piezoelectric response observed in stretched PbTiO_{3} results from small-angle rotations dipoles walls, distinct conventional polarization rotation mechanism adaptive inferred static structures. We identify structure, termed "dipole spiral," which exhibits giant intrinsic (>320 pC/N). This helical possessing rotational zero-energy mode, unlocks new possibilities chiral phonon Dzyaloshinskii-Moriya-like interactions.

Language: Английский

---

Origin of Interstitial Doping Induced Coercive Field Reduction in Ferroelectric Hafnia

Physical Review Letters, Journal Year: 2025, Volume and Issue: 134(5)

Published: Feb. 4, 2025

Hafnia-based ferroelectrics hold promise for nonvolatile ferroelectric memory devices. However, the high coercive field required polarization switching remains a prime obstacle to their practical applications. A notable reduction in has been achieved Hf(Zr)_{1+x}O_{2} films with interstitial Hf(Zr) dopants [Science 381, 558 (2023)SCIEAS0036-807510.1126/science.adf6137], suggesting less-explored strategy optimization. Supported by density functional theory calculations, we demonstrate Pca2_{1} phase, moderate concentration of Hf dopants, serves as minimal model explain experimental observations, rather than originally assumed rhombohedral phase. Large-scale deep potential molecular dynamics simulations suggest that defects promote reversal facilitating Pbcn-like mobile 180° domain walls. simple prepoling treatment could reduce less 1 MV/cm and enable on subnanosecond timescale. High-throughput calculations reveal negative correlation between barrier dopant size identify few promising reduction.

Language: Английский

---

Domain-Wall Enhanced Pyroelectricity

Physical Review X, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 18, 2025

Ferroelectric domain walls are not just static geometric boundaries between polarization domains; they are, in fact, dynamic and functional interfaces with the potential for diverse technological applications. While roles of ferroelectric dielectric piezoelectric responses better understood, their impact on pyroelectric response remains underexplored. Here, (001)-, (101)-, (111)-oriented epitaxial heterostructures tetragonal PbZr0.2Ti0.8O3 is probed. These differently oriented exhibit same type 90° ferroelastic walls, but geometry density vary orientation. In turn, piezoresponse force microscopy direct measurements reveal that both highest coefficients. By varying thickness these (from 100 to 280 nm), can be varied, a correlation domain-wall coefficients found. Molecular-dynamics simulations confirm findings novel contribution volume material or near exhibits significantly higher coefficient as compared bulk domains. Analysis suggests has responsivity external fields temperature. This study sheds light microscopic origin contributions pyroelectricity provides pathway controlling this effect. Published by American Physical Society 2025

Language: Английский

---

Progress in computational understanding of ferroelectric mechanisms in HfO2

npj Computational Materials, Journal Year: 2024, Volume and Issue: 10(1)

Published: Aug. 23, 2024

Abstract Since the first report of ferroelectricity in nanoscale HfO 2 -based thin films 2011, this silicon-compatible binary oxide has quickly garnered intense interest academia and industry, continues to do so. Despite its deceivingly simple chemical composition, ferroelectric physics supported by is remarkably complex, arguably rivaling that perovskite ferroelectrics. Computational investigations, especially those utilizing first-principles density functional theory (DFT), have significantly advanced our understanding nature these films. In review, we provide an in-depth discussion computational efforts understand hafnia, comparing various metastable polar phases examining critical factors necessary for their stabilization. The intricate intimately related complex interplay among diverse structural polymorphs, dopants charge-compensating oxygen vacancies, unconventional switching mechanisms domains domain walls, which can sometimes yield conflicting theoretical predictions theoretical-experimental discrepancies. We also discuss opportunities enabled machine-learning-assisted molecular dynamics phase-field simulations go beyond DFT modeling, probing dynamical properties tackling pressing issues such as high coercive fields.

Language: Английский

---

Ferroelastic Twin-Wall-Mediated Ferroelectriclike Behavior and Bulk Photovoltaic Effect in SrTiO3

Physical Review Letters, Journal Year: 2024, Volume and Issue: 132(17)

Published: April 26, 2024

Ferroelastic twin walls in nonpolar materials can give rise to a spontaneous polarization due symmetry breaking. Nevertheless, the bistable polarity of and its reversal have not yet been demonstrated. Here, we report that ${\text{SrTiO}}_{3}$ be switched by an ultralow strain gradient. Using first-principles-based machine-learning potential, demonstrate deterministically rotated realigned specific directions under gradient, which breaks inversion sequence leads macroscopic polarization. The system maintain even after constraint is removed. As result, exhibit ferroelectriclike hysteresis loop upon cyclic bending, namely flexoferroelectricity. Finally, propose scheme experimentally detect wall measuring bulk photovoltaic responses. Our findings suggest twin-wall-mediated flexoferroelectricity ${\text{SrTiO}}_{3}$, could potentially exploited as functional elements nanoelectronic devices design.

Language: Английский

---

Universal interatomic potential for perovskite oxides

Physical review. B./Physical review. B, Journal Year: 2023, Volume and Issue: 108(18)

Published: Nov. 13, 2023

With their celebrated structural and chemical flexibility, perovskite oxides have served as a highly adaptable material platform for exploring emergent phenomena arising from the interplay between different degrees of freedom. Molecular dynamics (MD) simulations leveraging classical force fields, commonly depicted parametrized analytical functions, made significant contributions in elucidating atomistic properties crystalline solids including oxides. However, fields currently available are rather specific offer limited transferability, making it time-consuming to use MD study new materials systems since field must be tested first. The lack generalized applicable broad spectrum solid hinders facile deployment computer-aided discovery (CAMD). Here, by utilizing deep-neural network with self-attention scheme, we developed unified (UniPero) that enables involving 14 metal elements conceivably solutions arbitrary compositions. Notably, isobaric-isothermal ensemble this model potential accurately predict experimental temperature-driven phase transition sequences several markedly ferroelectric oxides, six-element ternary solution $\mathrm{Pb}({\mathrm{In}}_{1/2}{\mathrm{Nb}}_{1/2}){\mathrm{O}}_{3}\text{--}\mathrm{Pb}({\mathrm{Mg}}_{1/3}{\mathrm{Nb}}_{2/3}){\mathrm{O}}_{3}\text{--}{\mathrm{PbTiO}}_{3}$. We believe universal interatomic along training database, proposed regression tests, auto-testing workflow, all released publicly, will pave way systematic improvement extension solids, potentially heralding era CAMD.

Language: Английский

---

Implementation and Validation of an OpenMM Plugin for the Deep Potential Representation of Potential Energy

International Journal of Molecular Sciences, Journal Year: 2024, Volume and Issue: 25(3), P. 1448 - 1448

Published: Jan. 24, 2024

Machine learning potentials, particularly the deep potential (DP) model, have revolutionized molecular dynamics (MD) simulations, striking a balance between accuracy and computational efficiency. To facilitate DP model’s integration with popular MD engine OpenMM, we developed versatile OpenMM plugin. This plugin supports range of applications, from conventional simulations to alchemical free energy calculations hybrid DP/MM simulations. Our extensive validation tests encompassed conservation in microcanonical ensemble fidelity canonical generation, evaluation structural, transport, thermodynamic properties bulk water. The introduction this is expected significantly expand application scope models within simulation community, representing major advancement field.

Language: Английский

---

Machine learning assisted composition design of high-entropy Pb-free relaxors with giant energy-storage

Nature Communications, Journal Year: 2025, Volume and Issue: 16(1)

Published: Feb. 1, 2025

Abstract The high-entropy strategy has emerged as a prevalent approach to boost capacitive energy-storage performance of relaxors for advanced electrical and electronic systems. However, exploring high-performance systems poses challenges due the extensive compositional space. Herein, with assistance machine learning screening, we demonstrated high density 20.7 J cm -3 efficiency 86% in Pb-free relaxor ceramic. A random forest regression model key descriptors based on limited reported experimental data were developed predict screen elements chemical compositions Following basic experiments, (Bi 0.5 Na )TiO 3 -based characterized by fine grains, weakly-coupled small-sized polar clusters was identified. This resulted near-linear polarization behavior an ultrahigh breakdown strength 95 kV mm -1 . Further, this realxor presented discharge energy 7.7 under rate about 27 ns, along superior temperature fatigue stability. Our results present data-driven efficiently relaxors, demonstrating potential developing relaxors.

Language: Английский

---

Multimodal deep learning-driven exploration of lanthanide-based perovskite oxide semiconductors for ultra-sensitive detection of 2-butanone

Chemical Engineering Journal, Journal Year: 2025, Volume and Issue: unknown, P. 162154 - 162154

Published: March 1, 2025

Language: Английский

---