A liquid optical memristor using photochromic effect and capillary effect

Dingchen Wang; Anran Yuan; Shilei Dai; Xiao Tang; Kunbin Huang; Songrui Wei; Han Zhang; Zhongrui Wang

doi:10.1088/2634-4386/ad5fb2

Neuromorphic Computing and Engineering (Jan 2024)

A liquid optical memristor using photochromic effect and capillary effect

Dingchen Wang,
Anran Yuan,
Shilei Dai,
Xiao Tang,
Kunbin Huang,
Songrui Wei,
Han Zhang,
Zhongrui Wang

Affiliations

Dingchen Wang: ORCiD; Department of Electrical and Electronic Engineering, The University of Hong Kong , Pokfulam Road, Hong Kong Special Administrative Region of China, People’s Republic of China; ACCESS—AI Chip Center for Emerging Smart Systems, InnoHK Centers, Hong Kong Science Park , Hong Kong Special Administrative Region of China, People’s Republic of China
Anran Yuan: Faculty of Innovation Engineering, School of Computer Science and Engineering, Macau University of Science and Technology , Macau, People’s Republic of China
Shilei Dai: Department of Electrical and Electronic Engineering, The University of Hong Kong , Pokfulam Road, Hong Kong Special Administrative Region of China, People’s Republic of China
Xiao Tang: Collaborative Innovation Center for Optoelectronic Science Technology, International Collaborative Laboratory of 2D Materials for Optoelectronics, Science and Technology of Ministry of Education , Shenzhen, People’s Republic of China; Institute of Microscale Optoelectronics, Shenzhen University , Shenzhen, People’s Republic of China
Kunbin Huang: Collaborative Innovation Center for Optoelectronic Science Technology, International Collaborative Laboratory of 2D Materials for Optoelectronics, Science and Technology of Ministry of Education , Shenzhen, People’s Republic of China; Institute of Microscale Optoelectronics, Shenzhen University , Shenzhen, People’s Republic of China
Songrui Wei: Collaborative Innovation Center for Optoelectronic Science Technology, International Collaborative Laboratory of 2D Materials for Optoelectronics, Science and Technology of Ministry of Education , Shenzhen, People’s Republic of China; Institute of Microscale Optoelectronics, Shenzhen University , Shenzhen, People’s Republic of China
Han Zhang: ORCiD; Collaborative Innovation Center for Optoelectronic Science Technology, International Collaborative Laboratory of 2D Materials for Optoelectronics, Science and Technology of Ministry of Education , Shenzhen, People’s Republic of China; Institute of Microscale Optoelectronics, Shenzhen University , Shenzhen, People’s Republic of China
Zhongrui Wang: ORCiD; Department of Electrical and Electronic Engineering, The University of Hong Kong , Pokfulam Road, Hong Kong Special Administrative Region of China, People’s Republic of China; ACCESS—AI Chip Center for Emerging Smart Systems, InnoHK Centers, Hong Kong Science Park , Hong Kong Special Administrative Region of China, People’s Republic of China

DOI: https://doi.org/10.1088/2634-4386/ad5fb2
Journal volume & issue: Vol. 4, no. 3
p. 034003

Abstract

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In the era of the Internet of Things, photonic neuromorphic computing presents a promising method for real-time, local processing of vast quantities of data. However, the rigidity of materials used in such devices can considerably impact performance and longevity when subjected to mechanical deformation. In this study, we introduce a liquid optical memristor (LOM) based on an organic-inorganic hybrid in a liquid state. This novel approach offers programmable optical properties and significant mechanical flexibility thanks to the robust photochromic and capillary effects. We have developed a LOM with a 24 dB cm ^−1 modulation depth and over 3-bit nonvolatile memory states. By controlling the droplet morphology to mimic a synapse-like shape, the LOM can withstand strains over 400% and endure misalignment and bending. Furthermore, our findings substantiate the application of LOM for photonic neuromorphic computing systems, yielding 100% accuracy in pattern recognition. The easily-integratable LOM paves the way for the creation of flexible and wearable photonic neuromorphic computing systems.

Published in Neuromorphic Computing and Engineering

ISSN: 2634-4386 (Online)
Publisher: IOP Publishing
Country of publisher: United Kingdom
LCC subjects: Science: Mathematics: Instruments and machines: Electronic computers. Computer science
Website: https://iopscience.iop.org/journal/2634-4386

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