Photo‐Induced Oxygen Vacancy Modulation in Solution‐Processed TiO <sub>2</sub> /ZnFe <sub>2</sub> O <sub>4</sub> Heterointerface for Dual‐Mode Synaptic Memory
ABSTRACT The rapid advancements and growing demand for energy‐efficient, parallel information processing have accelerated research into brain‐inspired neuromorphic computing. Memristors, with their ability to switch between resistance states and emulate synaptic plasticity, are promising candidates in replicating biological synapses. However, conventional devices are largely restricted to either electrical or optical operation, limiting multimodal functionality, commonly observed in the nervous system. Integrating oxides via solution processing to design a heterojunction memristor that exhibits multimodal synaptic plasticity can be an ideal alternative for cost‐effective, stable, and multifunctional parallel computing, emulating the human brain. Here, we prepared a spin‐coated TiO 2 /ZnFe 2 O 4 heterojunction that shows analog switching with gradual conductance modulation, governed by a confined conductive filament across the junction. The device effectively mimics synaptic behaviors like potentiation/depression, short‐term/long‐term memory, and paired‐pulse facilitation, under both electrical and optical stimuli. Ultraviolet photoelectron spectroscopy combined with the X‐ray photoelectron spectroscopy studies before and after illumination suggests that light‐driven oxygen‐vacancy modulation determines the tunneling current through the heterointerface, resulting in persistent photo‐response and optical synaptic plasticity. In addition to conventional functionalities like Morse code reading, Pavlov's classical conditioning, the multimodal adaptability facilitates our device to perform configurable logic operations, showing efficient and biologically realistic pathways for next‐generation neuromorphic computing.
Authors
- Priya Kaith (ORCID: https://orcid.org/0000-0001-6634-8526)
- Ashok Bera (ORCID: https://orcid.org/0000-0003-2650-8884)
- Faisal Farooq
Institutions
- Indian Institute of Technology Jammu (IN)
Publication Details
- Journal
- Advanced Materials Technologies
- Published
- 2026-04-17
- DOI
- https://doi.org/10.1002/admt.70995
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Department of Science and Technology, Government of Kerala
- Science and Engineering Research Board