Artificial synapse‐based intelligent light‐controlled liquid crystal network actuators

Abstract Various forms of intelligent light‐controlled soft actuators and robots rely on advanced material architectures and bionic systems to enable programmable remote actuation and multifunctionality. Despite advancements, significant challenges remain in developing actuators and robots that can...

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Main Authors: Yuhang Song, Junyao Zhang, Zejun Sun, Haixia Liang, Tongrui Sun, Zhimin Lu, Shucong Li, Yuxing Yao, Xiaoguang Wang, Yang Xu, Jia Huang
Format: Article
Language:English
Published: Wiley 2025-06-01
Series:InfoMat
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Online Access:https://doi.org/10.1002/inf2.70008
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author Yuhang Song
Junyao Zhang
Zejun Sun
Haixia Liang
Tongrui Sun
Zhimin Lu
Shucong Li
Yuxing Yao
Xiaoguang Wang
Yang Xu
Jia Huang
author_facet Yuhang Song
Junyao Zhang
Zejun Sun
Haixia Liang
Tongrui Sun
Zhimin Lu
Shucong Li
Yuxing Yao
Xiaoguang Wang
Yang Xu
Jia Huang
author_sort Yuhang Song
collection DOAJ
description Abstract Various forms of intelligent light‐controlled soft actuators and robots rely on advanced material architectures and bionic systems to enable programmable remote actuation and multifunctionality. Despite advancements, significant challenges remain in developing actuators and robots that can effectively mimic the low‐intensity, wide‐wavelength light signal sensing and processing functions observed in living organisms. Herein, we report a design strategy that integrates light‐responsive artificial synapses (AS) with liquid crystal networks (LCNs) to create bionic light‐controlled LCN soft actuators (AS‐LCNs). Remarkably, AS‐LCNs can be controlled with light intensities as low as 0.68 mW cm−2, a value comparable to the light intensity perceivable by the human eye. These AS‐LCNs can perform programmable intelligent sensing, learning, and memory within a wide wavelength range from 365 nm to 808 nm. Additionally, our system demonstrates time‐related proofs of concept for a tachycardia alarm and a porcupine defense behavior simulation. Overall, this work addresses the limitations of traditional light‐controlled soft actuators and robots in signal reception and processing, paving the way for the development of intelligent soft actuators and robots that emulate the cognitive abilities of living organisms.
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spelling doaj-art-fbf2950ef4b9488db5dd279e87f8b79f2025-08-20T02:40:28ZengWileyInfoMat2567-31652025-06-0176n/an/a10.1002/inf2.70008Artificial synapse‐based intelligent light‐controlled liquid crystal network actuatorsYuhang Song0Junyao Zhang1Zejun Sun2Haixia Liang3Tongrui Sun4Zhimin Lu5Shucong Li6Yuxing Yao7Xiaoguang Wang8Yang Xu9Jia Huang10School of Materials Science and Engineering Tongji University Shanghai the People's Republic of ChinaSchool of Materials Science and Engineering Tongji University Shanghai the People's Republic of ChinaSchool of Materials Science and Engineering Tongji University Shanghai the People's Republic of ChinaSchool of Materials Science and Engineering Tongji University Shanghai the People's Republic of ChinaSchool of Materials Science and Engineering Tongji University Shanghai the People's Republic of ChinaSchool of Materials Science and Engineering Tongji University Shanghai the People's Republic of ChinaSchool of Engineering Massachusetts Institute of Technology Cambridge Massachusetts USADivision of Chemistry and Chemical Engineering California Institute of Technology Pasadena California USAWilliam G. Lowrie Department of Chemical and Biomolecular Engineering The Ohio State University Columbus Ohio USASchool of Materials Science and Engineering Tongji University Shanghai the People's Republic of ChinaSchool of Materials Science and Engineering Tongji University Shanghai the People's Republic of ChinaAbstract Various forms of intelligent light‐controlled soft actuators and robots rely on advanced material architectures and bionic systems to enable programmable remote actuation and multifunctionality. Despite advancements, significant challenges remain in developing actuators and robots that can effectively mimic the low‐intensity, wide‐wavelength light signal sensing and processing functions observed in living organisms. Herein, we report a design strategy that integrates light‐responsive artificial synapses (AS) with liquid crystal networks (LCNs) to create bionic light‐controlled LCN soft actuators (AS‐LCNs). Remarkably, AS‐LCNs can be controlled with light intensities as low as 0.68 mW cm−2, a value comparable to the light intensity perceivable by the human eye. These AS‐LCNs can perform programmable intelligent sensing, learning, and memory within a wide wavelength range from 365 nm to 808 nm. Additionally, our system demonstrates time‐related proofs of concept for a tachycardia alarm and a porcupine defense behavior simulation. Overall, this work addresses the limitations of traditional light‐controlled soft actuators and robots in signal reception and processing, paving the way for the development of intelligent soft actuators and robots that emulate the cognitive abilities of living organisms.https://doi.org/10.1002/inf2.70008actuatorsartificial intelligenceartificial synapsesliquid crystal networksrobots
spellingShingle Yuhang Song
Junyao Zhang
Zejun Sun
Haixia Liang
Tongrui Sun
Zhimin Lu
Shucong Li
Yuxing Yao
Xiaoguang Wang
Yang Xu
Jia Huang
Artificial synapse‐based intelligent light‐controlled liquid crystal network actuators
InfoMat
actuators
artificial intelligence
artificial synapses
liquid crystal networks
robots
title Artificial synapse‐based intelligent light‐controlled liquid crystal network actuators
title_full Artificial synapse‐based intelligent light‐controlled liquid crystal network actuators
title_fullStr Artificial synapse‐based intelligent light‐controlled liquid crystal network actuators
title_full_unstemmed Artificial synapse‐based intelligent light‐controlled liquid crystal network actuators
title_short Artificial synapse‐based intelligent light‐controlled liquid crystal network actuators
title_sort artificial synapse based intelligent light controlled liquid crystal network actuators
topic actuators
artificial intelligence
artificial synapses
liquid crystal networks
robots
url https://doi.org/10.1002/inf2.70008
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