Bio‐Inspired Organic Synaptor with In Situ Ion‐Doped Ultrathin Polyelectrolyte Containing Acetylcholine‐Like Cation

Author:

Yu Ji‐Man1,Kim Youson2,Lee Changhyeon2,Jeong Booseok2,Kim Jin‐Ki1,Han Joon‐Kyu3,Yang Junyeong2,Yun Seong‐Yun1,Im Sung Gap2,Choi Yang‐Kyu1ORCID

Affiliation:

1. School of Electrical Engineering Korea Advanced Institute of Science and Technology (KAIST) 291 Daehak‐ro, Yuseong‐gu Daejeon 34141 Republic of Korea

2. Department of Chemical and Biomolecular Engineering KAIST 291 Daehak‐ro, Yuseong‐gu Daejeon 34141 Republic of Korea

3. System Semiconductor Engineering and Department of Electronic Engineering Sogang University 35 Baekbeom‐ro, Mapo‐gu Seoul 04107 Republic of Korea

Abstract

AbstractAn ion‐based synaptic transistor (synaptor) is designed to emulate a biological synapse using controlled ion movements. However, developing a solid‐state electrolyte that can facilitate ion movement while achieving large‐scale integration remains challenging. Here, a bio‐inspired organic synaptor (BioSyn) with an in situ ion‐doped polyelectrolyte (i‐IDOPE) is demonstrated. At the molecular scale, a polyelectrolyte containing the tert‐amine cation, inspired by the neurotransmitter acetylcholine is synthesized using initiated chemical vapor deposition (iCVD) with in situ doping, a one‐step vapor‐phase deposition used to fabricate solid‐state electrolytes. This method results in an ultrathin, but highly uniform and conformal solid‐state electrolyte layer compatible with large‐scale integration, a form that is not previously attainable. At a synapse scale, synapse functionality is replicated, including short‐term and long‐term synaptic plasticity (STSP and LTSP), along with a transformation from STSP to LTSP regulated by pre‐synaptic voltage spikes. On a system scale, a reflex in a peripheral nervous system is mimicked by mounting the BioSyns on various substrates such as rigid glass, flexible polyethylene naphthalate, and stretchable poly(styrene‐ethylene‐butylene‐styrene) for a decentralized processing unit. Finally, a classification accuracy of 90.6% is achieved through semi‐empirical simulations of MNIST pattern recognition, incorporating the measured LTSP characteristics from the BioSyns.

Funder

National Research Foundation of Korea

KAIST Wearable Platform Material Technology Center

Publisher

Wiley

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3