Dynamic resistive switching of WOx-based memristor for associative learning activities, on-receptor, and reservoir computing

Minseo Noh, Hyogeun Park and Sungjun Kim

Chaos, Solitons & Fractals, 2025, vol. 196, issue C

Abstract: The rapid expansion of data driven by the fourth industrial revolution has revealed significant limitations in conventional computing architectures, particularly in their ability to efficiently process vast amounts of data. Neuromorphic computing, which draws inspiration from the brain's parallel processing capabilities and efficiency, presents a promising solution to overcome these limitations. This study introduces a TiN/WOx/Pt memory device capable of emulating both nociceptive and synaptic behaviors, highlighting its potential for neuromorphic computing applications. The device successfully replicates key nociceptive functions, including threshold response, allodynia, and hyperalgesia, through the migration of oxygen ions and vacancies within the interface. Furthermore, it demonstrates a range of synaptic plasticity behaviors, such as spike-number-dependent plasticity, spike-amplitude-dependent plasticity, spike-rate-dependent plasticity, and paired-pulse facilitation. In addition, the device achieves 4-bit multibit reservoir computing with high accuracy, showcasing its ability to perform adaptive learning and nonlinear data processing. These results underline the TiN/WOx/Pt memory device's promise for mimicking biological functions and its significant potential in the development of advanced neuromorphic computing systems.

Keywords: Dynamic memristor; Associative learning; On-receptor computing; Reservoir computing (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:196:y:2025:i:c:s0960077925003947

DOI: 10.1016/j.chaos.2025.116381

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