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Automated Experiments of Local Non-Linear Behavior in Ferroelectric Materials.

Authors :
Liu Y
Kelley KP
Vasudevan RK
Zhu W
Hayden J
Maria JP
Funakubo H
Ziatdinov MA
Trolier-McKinstry S
Kalinin SV
Source :
Small (Weinheim an der Bergstrasse, Germany) [Small] 2022 Dec; Vol. 18 (48), pp. e2204130. Date of Electronic Publication: 2022 Oct 17.
Publication Year :
2022

Abstract

An automated experiment in multimodal imaging to probe structural, chemical, and functional behaviors in complex materials and elucidate the dominant physical mechanisms that control device function is developed and implemented. Here, the emergence of non-linear electromechanical responses in piezoresponse force microscopy (PFM) is explored. Non-linear responses in PFM can originate from multiple mechanisms, including intrinsic material responses often controlled by domain structure, surface topography that affects the mechanical phenomena at the tip-surface junction, and the presence of surface contaminants. Using an automated experiment to probe the origins of non-linear behavior in ferroelectric lead titanate (PTO) and ferroelectric Al <subscript>0.93</subscript> B <subscript>0.07</subscript> N films, it is found that PTO shows asymmetric nonlinear behavior across a/c domain walls and a broadened high nonlinear response region around c/c domain walls. In contrast, for Al <subscript>0.93</subscript> B <subscript>0.07</subscript> N, well-poled regions show high linear piezoelectric responses, when paired with low non-linear responses regions that are multidomain show low linear responses and high nonlinear responses. It is shown that formulating dissimilar exploration strategies in deep kernel learning as alternative hypotheses allows for establishing the preponderant physical mechanisms behind the non-linear behaviors, suggesting that automated experiments can potentially discern between competing physical mechanisms. This technique can also be extended to electron, probe, and chemical imaging.<br /> (© 2022 Wiley-VCH GmbH.)

Details

Language :
English
ISSN :
1613-6829
Volume :
18
Issue :
48
Database :
MEDLINE
Journal :
Small (Weinheim an der Bergstrasse, Germany)
Publication Type :
Academic Journal
Accession number :
36253123
Full Text :
https://doi.org/10.1002/smll.202204130