Ionic liquid multistate resistive switching characteristics in two terminal soft and flexible discrete channels for neuromorphic computing

Muhammad Umair Khan, Jungmin Kim, Mahesh Y. Chougale, Chaudhry Muhammad Furqan, Qazi Muhammad Saqib, Rayyan Ali Shaukat, Nobuhiko P. Kobayashi, Baker Mohammad, Jinho Bae, Hoi Sing Kwok

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

By exploiting ion transport phenomena in a soft and flexible discrete channel, liquid material conductance can be controlled by using an electrical input signal, which results in analog neuromorphic behavior. This paper proposes an ionic liquid (IL) multistate resistive switching device capable of mimicking synapse analog behavior by using IL BMIM FeCL4 and H2O into the two ends of a discrete polydimethylsiloxane (PDMS) channel. The spike rate-dependent plasticity (SRDP) and spike-timing-dependent plasticity (STDP) behavior are highly stable by modulating the input signal. Furthermore, the discrete channel device presents highly durable performance under mechanical bending and stretching. Using the obtained parameters from the proposed ionic liquid-based synaptic device, convolutional neural network simulation runs to an image recognition task, reaching an accuracy of 84%. The bending test of a device opens a new gateway for the future of soft and flexible brain-inspired neuromorphic computing systems for various shaped artificial intelligence applications.

Original languageBritish English
Article number56
JournalMicrosystems and Nanoengineering
Volume8
Issue number1
DOIs
StatePublished - Dec 2022

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