Ferroelectric Domain Wall Warp Memristor

Domain walls are quasi-one-dimensional topological defects in ferroic materials, which can harbor emergent functionalities. In the case of ferroelectric domain wall (FEDW) devices, an exciting frontier has emerged: memristor-based information storage and processing approaches. Memristor solid-state FEDW devices presented thus far, however predominantly utilize a complex network of domain walls to achieve the desired regulation of density and charge state. Here, using epitaxial bismuth ferrite thin films as a prototype ferroelectric and advanced scanning probe microscopy and stroboscopic methods, we demonstrate controlled single-wall memristive behavior through deterministic electric field-driven conformal changes. Our design exploits memristive functionality through surface pinning of topological domain walls. That is, although the FEDW is constricted by the surface, it is free to twist in the thickness direction. The resulting vertical variation of FEDW morphology creates a complex interplay between surface-induced pinning and field-induced wall bending. This gives rise to metastable electronic transitions, and hence memristive attributes. Moreover, being a single FEDW memristor, once injected there is no need for repeated injection or erasure. Microscopic insight into device operation from phase field modeling indicates controllable warping of the wall, causing memristive conductivity changes. Our results reaffirm the promise of FEDWS for brain-inspired neuromorphic and in-memory computing applications based on integrated ferroelectric devices.

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Publication Details

Journal
ACS Applied Materials & Interfaces
Published
2024-12-23
DOI
https://doi.org/10.1021/acsami.4c16347
Citations
4
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.83

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article

Ferroelectric Domain Wall Warp Memristor

Yunya Liu, Pankaj Kumar Sharma, Daniel Sando, Chihou Lei et al.
4 citations
ACS Applied Materials & Interfaces
Advanced Memory and Neural Computing
0.83
article

Ferroelectric Domain Wall Warp Memristor

Yunya Liu, Pankaj Kumar Sharma, Daniel Sando, Chihou Lei, V. Nagarajan, Jan Seidel, Qi Zhang
article en
4 citations

Abstract

Domain walls are quasi-one-dimensional topological defects in ferroic materials, which can harbor emergent functionalities. In the case of ferroelectric domain wall (FEDW) devices, an exciting frontier has emerged: memristor-based information storage and processing approaches. Memristor solid-state FEDW devices presented thus far, however predominantly utilize a complex network of domain walls to achieve the desired regulation of density and charge state. Here, using epitaxial bismuth ferrite thin films as a prototype ferroelectric and advanced scanning probe microscopy and stroboscopic methods, we demonstrate controlled single-wall memristive behavior through deterministic electric field-driven conformal changes. Our design exploits memristive functionality through surface pinning of topological domain walls. That is, although the FEDW is constricted by the surface, it is free to twist in the thickness direction. The resulting vertical variation of FEDW morphology creates a complex interplay between surface-induced pinning and field-induced wall bending. This gives rise to metastable electronic transitions, and hence memristive attributes. Moreover, being a single FEDW memristor, once injected there is no need for repeated injection or erasure. Microscopic insight into device operation from phase field modeling indicates controllable warping of the wall, causing memristive conductivity changes. Our results reaffirm the promise of FEDWS for brain-inspired neuromorphic and in-memory computing applications based on integrated ferroelectric devices.

ACS Applied Materials & InterfacesVol. 17(1)
University of Scranton (US), Flinders University (AU), University of Canterbury (NZ), UNSW Sydney (AU), ARC Centre of Excellence in Future Low-Energy Electronics Technologies (AU), Division of Materials Science and Engineering (AU), CSIRO Manufacturing (AU), Xiangtan University (CN)
Australian National Fabrication Facility, Australian Government, Flinders University, National Natural Science Foundation of China, Science and Technology Program of Hunan Province, Australian Research Council
Affordable and clean energy
Openalex Percentile: Top 26%
Advanced Memory and Neural Computing
0.83
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