journal article·2025-11-26

Exploring Domain-Wall Pinning in Ferroelectrics via Automated High-Throughput Atomic Force Microscopy

Kamyar Barakati, Yu Liu, Hiroshi Funakubo, Sergei V. Kalinin

ACS Applied Materials & Interfaces· Volume 17· Issue 47
Publisher page

Abstract

Domain-wall dynamics in ferroelectric materials are strongly position-dependent, since each polar interface is locked into a unique local microstructure. This necessitates spatially resolved studies of wall pinning using scanning-probe microscopy techniques. The pinning centers and pre-existing domain walls are usually sparse within the image plane, precluding the use of dense hyperspectral imaging modes and requiring time-consuming human experimentation. Here, a large-area epitaxial PbTiO 3 film on cubic KTaO 3 was investigated to quantify the electric-field-driven dynamics of the polar–strain domain structures using ML-controlled automated piezoresponse force microscopy. Analysis of 1500 switching events reveals that domain-wall displacement depends not only on field parameters but also on the local ferroelectric–ferroelastic configuration. For example, twin boundaries in polydomains regions, like a 1 – / c + ∥ a 2 – / c –, stay pinned up to a certain level of bias magnitude and change only marginally as the bias increases from 20 to 30 V, whereas single-variant boundaries, like the a 2 + / c + ∥ a 2 – / c – stack, are already activated at 20 V. These statistics on the possible ferroelectric and ferroelastic wall orientations, together with the automated high-throughput AFM workflow, can be distilled into a predictive map that links domain configurations to pulse parameters. This microstructure-specific rule set forms the foundation for the design of ferroelectric memories.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Ferroelectric and Piezoelectric Materials · Photorefractive and Nonlinear Optics · Force Microscopy Techniques and Applications

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Materials Science and Engineering

University of Tennessee

Tokyo Institute of Technology

Pacific Northwest National Laboratory

Funding

Ministry of Education, Culture, Sports, Science and Technology · U.S. Department of Energy

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