Experimental and theoretical study of solid–solid dendrite domain growth in uniaxial ferroelectrics

Dendrite patterns appear in a wide range of natural phenomena, from metal castings to bacterial colonies and snowflakes. Significant efforts have been devoted to creating new experimental systems demonstrating dendrite growth that can be used as models for deep experimental study of the process. Here, we show the formation of ferroelectric dendrite domains during polarization reversal under nonequilibrium conditions. We achieved dendrite growth in lithium niobate LiNbO3 crystals with an artificial surface dielectric layer at elevated temperatures. The nonequilibrium switching conditions caused by incomplete screening of the depolarization field suppress the usual faceted domain growth. Up to six branching generations were observed, with a branch width below 100 nm. In situ optical imaging allowed dendrite evolution to be studied at millisecond temporal resolution. Our investigation into dendrite formation was based on an analogy between crystal and domain growth. Upon development of a corresponding computational model, we demonstrated that uniaxial ferroelectrics represent a promising model system for the experimental study of dendrite growth. Likewise, a wide range of driving parameters and a high spatial resolution help provide new insights into the general laws of the formation of dendrite patterns.

Authors

Institutions

Publication Details

Journal
Applied Physics Reviews
Published
2026-01-29
DOI
https://doi.org/10.1063/5.0285675
Primary Topic
Ferroelectric and Piezoelectric Materials
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Experimental and theoretical study of solid–solid dendrite domain growth in uniaxial ferroelectrics

D. S. Chezganov, M. A. Chuvakova, A. R. Akhmatkhanov, V. Ya. Shur et al.
Applied Physics Reviews
Ferroelectric and Piezoelectric Materials
article

Experimental and theoretical study of solid–solid dendrite domain growth in uniaxial ferroelectrics

D. S. Chezganov, M. A. Chuvakova, A. R. Akhmatkhanov, V. Ya. Shur, A. A. Esin, M. S. Nebogatikov, E. D. Savelyev
article en

Abstract

Dendrite patterns appear in a wide range of natural phenomena, from metal castings to bacterial colonies and snowflakes. Significant efforts have been devoted to creating new experimental systems demonstrating dendrite growth that can be used as models for deep experimental study of the process. Here, we show the formation of ferroelectric dendrite domains during polarization reversal under nonequilibrium conditions. We achieved dendrite growth in lithium niobate LiNbO3 crystals with an artificial surface dielectric layer at elevated temperatures. The nonequilibrium switching conditions caused by incomplete screening of the depolarization field suppress the usual faceted domain growth. Up to six branching generations were observed, with a branch width below 100 nm. In situ optical imaging allowed dendrite evolution to be studied at millisecond temporal resolution. Our investigation into dendrite formation was based on an analogy between crystal and domain growth. Upon development of a corresponding computational model, we demonstrated that uniaxial ferroelectrics represent a promising model system for the experimental study of dendrite growth. Likewise, a wide range of driving parameters and a high spatial resolution help provide new insights into the general laws of the formation of dendrite patterns.

Applied Physics ReviewsVol. 13(1)
Ural Federal University (RU)
Openalex Percentile: Top 74%
Ferroelectric and Piezoelectric Materials
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.