Oxide Memristor of Ag/Ag <sup>+</sup> Doped V <sub>2</sub> O <sub>5</sub> and SnO <sub>2</sub> Bilayer Thin Film for Energy Efficient Memory, Logic and Neuromorphic Device Application

Abstract A solution‐processed, high‐performance bilayer‐structured memristor is developed by linking metallic and oxygen‐deficient channels. The device comprised a thin film of Ag(Ag⁺)‐V 2 O 5 , synthesized through Ag⁺ ion‐exchange and subsequent reduction of LiV 3 O 8 , sandwiched with a SnO 2 film followed by a 10 nm gold electrode, which also functions as light‐transmitting window. The memristor exhibits robust bipolar switching, sustaining over 3000 repeatable cycles with minimal degradation and pulse endurance approaching 10⁶ cycles. It achieves low‐to‐high resistance state ratio near 10⁵, and data retention exceeding 10⁵ s, maintaining an on/off ratio of ≈10⁴. Device‐to‐device uniformity is confirmed by intra‐batch variation within ±2% and inter‐batch variation across 50 fabrication runs within ±7%, highlighting excellent process reproducibility. Beyond standard ReRAM functions, the device supports logic operations and 4‐bit edge computing, validated across 20 intra and inter‐batch devices for operational reliability. Furthermore, it emulates long‐term synaptic plasticity under optical excitation, maintaining stable performance under ageing and repeated light on/off cycling, confirming strong environmental stability and reproducibility of the photo response behavior. Cyclic I–V sweeps induce potentiation and depression behavior, driving convolutional neural network‐based image recognition with ≈98% training accuracy. These results collectively position the bilayer architecture as a promising platform for multifunctional neuromorphic, logic, and optoelectronic applications.

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Publication Details

Journal
Advanced Functional Materials
Published
2025-09-23
DOI
https://doi.org/10.1002/adfm.202514732
Citations
4
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
2.92
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article

Oxide Memristor of Ag/Ag + Doped V 2 O 5 and SnO 2 Bilayer Thin Film for Energy Efficient Memory, Logic and Neuromorphic Device Application

Subarna Pramanik, Parasuraman Swaminathan, Bhola Nath Pal, Rajarshi Chakraborty et al.
4 citations
Advanced Functional Materials
Advanced Memory and Neural Computing
2.92
article

Oxide Memristor of Ag/Ag + Doped V 2 O 5 and SnO 2 Bilayer Thin Film for Energy Efficient Memory, Logic and Neuromorphic Device Application

Subarna Pramanik, Parasuraman Swaminathan, Bhola Nath Pal, Rajarshi Chakraborty, Swati Suman, Pushpendra Prakash Maurya
article en
4 citations

Abstract

Abstract A solution‐processed, high‐performance bilayer‐structured memristor is developed by linking metallic and oxygen‐deficient channels. The device comprised a thin film of Ag(Ag⁺)‐V 2 O 5 , synthesized through Ag⁺ ion‐exchange and subsequent reduction of LiV 3 O 8 , sandwiched with a SnO 2 film followed by a 10 nm gold electrode, which also functions as light‐transmitting window. The memristor exhibits robust bipolar switching, sustaining over 3000 repeatable cycles with minimal degradation and pulse endurance approaching 10⁶ cycles. It achieves low‐to‐high resistance state ratio near 10⁵, and data retention exceeding 10⁵ s, maintaining an on/off ratio of ≈10⁴. Device‐to‐device uniformity is confirmed by intra‐batch variation within ±2% and inter‐batch variation across 50 fabrication runs within ±7%, highlighting excellent process reproducibility. Beyond standard ReRAM functions, the device supports logic operations and 4‐bit edge computing, validated across 20 intra and inter‐batch devices for operational reliability. Furthermore, it emulates long‐term synaptic plasticity under optical excitation, maintaining stable performance under ageing and repeated light on/off cycling, confirming strong environmental stability and reproducibility of the photo response behavior. Cyclic I–V sweeps induce potentiation and depression behavior, driving convolutional neural network‐based image recognition with ≈98% training accuracy. These results collectively position the bilayer architecture as a promising platform for multifunctional neuromorphic, logic, and optoelectronic applications.

Advanced Functional MaterialsVol. 36(14)
Indian Institute of Technology Madras (IN), Banaras Hindu University (IN)
Openalex Percentile: Top 8%
Advanced Memory and Neural Computing
2.92
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