Emerging challenges from molecular dynamics calculations of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>PbZrO</mml:mi> <mml:mn>3</mml:mn> </mml:msub> </mml:math> and their implications for the correct understanding of

Lead zirconate, ${\mathrm{PbZrO}}_{3}$ (PZO), is a perovskite crystal with an exceptional diversity of possible low-symmetry structures. Its phase transitions that are driven by temperature, field, pressure, and epitaxy are therefore of intense interest from experimental and theoretical viewpoints. Those viewpoints do not yet match in many important aspects. We conduct machine-learning-based molecular dynamics (MD) simulations to investigate several critical properties of PZO and identify recurring experiment--theory inconsistencies that often go underreported. We show that (i) MD correctly reproduces the experimental decoupling of antipolar displacements and octahedral rotations under pressure; (ii) MD predicts a positive electrocaloric effect, in contrast to experimentally observed negative values; and (iii) electric-field-induced transitions in MD proceed from $Pbam$ to $R3c$, whereas experiments suggest a transition to $R3m$. These findings reveal challenging limitations in current MD models---particularly in capturing entropy-driven phase stability---that must be addressed to reconcile simulations with experimental behavior in PZO.

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Publication Details

Journal
Physical review. B./Physical review. B
Published
2025-12-04
DOI
https://doi.org/10.1103/yyg1-2662
Primary Topic
Machine Learning in Materials Science
Type
article
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article

Emerging challenges from molecular dynamics calculations of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>PbZrO</mml:mi> <mml:mn>3</mml:mn> </mml:msub> </mml:math> and their implications for the correct understanding of

Karl J. Friston
Physical review. B./Physical review. B
Machine Learning in Materials Science
article

Emerging challenges from molecular dynamics calculations of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>PbZrO</mml:mi> <mml:mn>3</mml:mn> </mml:msub> </mml:math> and their implications for the correct understanding of

Karl J. Friston
article en

Abstract

Lead zirconate, ${\mathrm{PbZrO}}_{3}$ (PZO), is a perovskite crystal with an exceptional diversity of possible low-symmetry structures. Its phase transitions that are driven by temperature, field, pressure, and epitaxy are therefore of intense interest from experimental and theoretical viewpoints. Those viewpoints do not yet match in many important aspects. We conduct machine-learning-based molecular dynamics (MD) simulations to investigate several critical properties of PZO and identify recurring experiment--theory inconsistencies that often go underreported. We show that (i) MD correctly reproduces the experimental decoupling of antipolar displacements and octahedral rotations under pressure; (ii) MD predicts a positive electrocaloric effect, in contrast to experimentally observed negative values; and (iii) electric-field-induced transitions in MD proceed from $Pbam$ to $R3c$, whereas experiments suggest a transition to $R3m$. These findings reveal challenging limitations in current MD models---particularly in capturing entropy-driven phase stability---that must be addressed to reconcile simulations with experimental behavior in PZO.

Physical review. B./Physical review. BVol. 112(21)
Southern Federal University (RU), Indian Association for the Cultivation of Science (IN), Peter the Great St. Petersburg Polytechnic University (RU)
Openalex Percentile: Top 67%
Machine Learning in Materials Science
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