Intrinsically Self‐Assembled SrFeO x Topotactic Phase Transition Memristor
ABSTRACT Topotactic phase‐transition (TPT) oxide memristors contain ordered 1D oxygen‐vacancy channels (OVCs) that enable anisotropic oxygen‐ion migration and reversible brownmillerite/perovskite transition, offering a materials platform for neuromorphic computing. However, the lack of spatially predefined oxygen‐ion migration sites in conventional TPT films promotes stochastic perovskite SrFeO 3 conductive filament (CF) growth, compromising the response stability and state distinguishability required for reliable temporal signal processing. Here, a single‐component self‐assembled SrFeO x memristor with alternating vertical and horizontal superlattice‐like OVC regions is reported. Structural characterization, density functional theory calculations, and kinetic Monte Carlo simulations indicate that this intrinsic self‐assembled architecture directs oxygen‐ion migration through vertical channels while horizontal regions restrict stray out‐of‐plane transport, promoting localized CF growth. The device combines forming‐free bipolar switching, an ON/OFF ratio of ∼4.4 × 10 3 , low cycle‐to‐cycle (C2C) variation with CV(V SET )/CV(V RESET ) of 3.2%/0.6%, 16‐state retention over 10 4 s, and endurance up to 10 7 pulse cycles. Reproducible device‐to‐device (D2D) switching is obtained across 32 cells, with D2D CV(V SET )/CV(V RESET ) values of 10.1%/5.9%. Finally, the device's short‐term memory transforms temporal inputs into distinguishable states that a fixed linear readout decodes with 84.59% accuracy on a temporal classification task. This work highlights intrinsic OVC‐orientation engineering as a materials‐level strategy toward reliable single‐component TPT memristors.
Authors
- Lei Ye (ORCID: https://orcid.org/0000-0001-5195-1867)
- Xiangshui Miao (ORCID: https://orcid.org/0000-0002-3999-7421)
- Kai Huang (ORCID: https://orcid.org/0000-0003-1919-8021)
- Rui Su (ORCID: https://orcid.org/0009-0006-5586-2048)
- Dunbao Chen
- Runqing Zhang
- Weiming Cheng
Institutions
- Guangdong Medical College (CN)
- Wuhan University of Technology (CN)
- Huazhong University of Science and Technology (CN)
Publication Details
- Journal
- Advanced Functional Materials
- Published
- 2026-11-06
- DOI
- https://doi.org/10.1002/adfm.79537
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Nanyang Technological University
- National Natural Science Foundation of China
- Natural Science Foundation of Hubei Province
- National Key Research and Development Program of China