Inkjet‐printed reconfigurable and recyclable memristors on paper

Abstract Reconfigurable memristors featuring neural and synaptic functions hold great potential for neuromorphic circuits by simplifying system architecture, cutting power consumption, and boosting computational efficiency. Building upon these attributes, their additive manufacturing on sustainable...

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Main Authors: Jinrui Chen, Mingfei Xiao, Zesheng Chen, Sibghah Khan, Saptarsi Ghosh, Nasiruddin Macadam, Zhuo Chen, Binghan Zhou, Guolin Yun, Kasia Wilk, Georgios Psaltakis, Feng Tian, Simon Fairclough, Yang Xu, Rachel Oliver, Tawfique Hasan
Format: Article
Language:English
Published: Wiley 2025-05-01
Series:InfoMat
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Online Access:https://doi.org/10.1002/inf2.70000
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Summary:Abstract Reconfigurable memristors featuring neural and synaptic functions hold great potential for neuromorphic circuits by simplifying system architecture, cutting power consumption, and boosting computational efficiency. Building upon these attributes, their additive manufacturing on sustainable substrates further offers unique advantages for future electronics, including low environmental impact. Here, exploiting the structure–property relationship of inkjet‐printed MoS2 nanoflake‐based resistive layer, we present paper‐based reconfigurable memristors. We demonstrate a sustainable process covering material exfoliation, device fabrication, and device recycling. With >90% yield from a 16 × 65 device array, our memristors demonstrate robust resistive switching, with >105 ON–OFF ratio and <0.5 V operation in non‐volatile state. Through modulation of compliance current, the devices transition into a volatile state, with only 50 pW switching power consumption. These performances rival state‐of‐the‐art metal oxide‐based counterparts. We show device recyclability and stable, reconfigurable operation following disassembly, material collection and re‐fabrication. We further demonstrate synaptic plasticity and neuronal leaky integrate‐and‐fire functionality, with disposable applications in smart packaging and simulated medical image diagnostics. Our work shows a sustainable pathway toward printable, reconfigurable neuromorphic devices, with minimal environmental footprints.
ISSN:2567-3165