Thermal and Size Effects in Ferroelastic Domains by Machine Learning
Luka Geddis Zellmann, Sumner B. Harris, John R. R. Scott, Yi-Chieh Yang, Joerg Jinschek, Rama Vasudevan, Miryam Arredondo

TL;DR
This study investigates how temperature and thickness influence ferroelastic domain wall behavior in LaAlO3 thin films, revealing a transition from mobile, curved walls near the transition temperature to static, less curved walls at room temperature.
Contribution
It introduces a machine-learning-based image analysis method to analyze domain wall dynamics across temperature and thickness regimes in ferroelastic thin films.
Findings
DWs are mobile and curved near T_C in the dipolar regime.
DWs become static and less curved at room temperature in the crossover regime.
Temperature and thickness jointly control DW morphology and dynamics.
Abstract
Ferroelastic domain walls (DWs) underpin key functionalities in complex oxides. In free-standing ferroic thin films, where elastic interactions are highly thickness dependent, understanding DW behaviour across length scales and external stimuli is crucial. A thickness-dependent monopolar-to-dipolar crossover in elastic DW behaviour has been reported; however, how temperature influences this regime remains unexplored. Here, LaAlO3 thin films spanning the dipolar ( nm) and crossover (200-300 nm) regimes are investigated using in situ heating scanning transmission electron microscopy (STEM) and a machine-learning-driven image analysis approach. By tracking DW curvature and density from above (approximately C) to room temperature (RT), a distinct interplay between temperature and thickness is identified. In the dipolar regime, DWs are mobile and curved near and…
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Taxonomy
TopicsFerroelectric and Piezoelectric Materials · Electronic and Structural Properties of Oxides · Ferroelectric and Negative Capacitance Devices
