한빛사 논문
Dae-Gyo Seoa,1, Yeongjun Leea,1, Gyeong-Tak Goa, Mingyuan Peib, Sungwoo Jungc, Yo Han Jeongd, Wanhee Leee, Hea-Lim Parka, Sang-Woo Kimd, Hoichang Yangb, Changduk Yangc, Tae-Woo Leea,f,*
a Department of Materials Science and Engineering, Seoul National University (SNU), Seoul, Republic of Korea
b Department of Chemical Engineering, Inha University, Incheon, 22212, Republic of Korea
c Department of Energy Engineering, School of Energy and Chemical Engineering, Perovtronics Research Center, Low Dimensional Carbon Materials Center, Ulsan National Institute of Science and Technology (UNIST), Ulsan, Republic of Korea
d School of Advanced Materials Science & Engineering, Sungkyunkwan University (SKKU), Suwon, Gyeonggi-do, Republic of Korea
e Department of Physics and Astronomy, Seoul National University (SNU), Seoul, Republic of Korea
f Department of Materials Science and Engineering, Institute of Engineering Research, Research Institute of Advanced Materials, BK21 PLUS SNU Materials Division for Educating Creative Global Leaders, Seoul National University (SNU), Seoul, Republic of Korea
1 These authors equally contributed to this work.
*Corresponding author : Tae-Woo Lee
Abstract
Organic neuromorphic electronics are inspired by a biological nervous system. Bio-inspired computing mimics learning and memory in a brain (i.e., the central nervous system), and bio-inspired soft robotics and nervous prosthetics mimics the neural signal transmission of afferent/efferent nerves (i.e., the peripheral nervous system). Synaptic decay time of nerves differ among biological organs, so the decay time of artificial synapses should be tuned for their specific uses in neuro-inspired electronics. However, controlling a synaptic decay constant in a fixed synaptic device geometry for broad applications was not been achieved in previous research of neuromorphic electronic devices despite the importance to achieve broad applications from neuromorphic computing to neuro-prosthetics. Here, we tailored the synaptic decay constant of organic synaptic transistors with fixed materials and devices structure rather than changing the form of presynaptic spikes, which enabled broad applications from neuromorphic computing to neuro-prosthetics. To achieve this, the relation between crystallinity of the polymer semiconductor film and the synaptic decay constant was revealed. The crystallinity of the polymer controlled electrochemical-doping kinetics and resultant synaptic behaviors of artificial synaptic transistors. In this way, we demonstrated not only long-term retention for learning and memory that is useful for neuromorphic computing in ion-gel gated organic synaptic transistor (IGOST) but also the short-term retention for fast synaptic transmission that is useful for emulating peripheral nerves such as sensory and motor nerve. To prove the feasibility of our approach in a two different ways, we first simulated pattern recognition on the MNIST dataset of handwritten digits using an IGOST with long-term retention due to increased crystallinity and then, developed artificial auditory sensory nerves that combines an IGOST with short term retention due to disordered chain morphology in a polymer semiconductor, with a triboelectric acoustic sensor. We expect that our approach will provide a universal strategy to realize wide neuromorphic electronic applications.
Keywords : Neuromorphic electronics; Artificial synapses; Neuromorphic computing; Artificial auditory systems; Artificial nerves
논문정보
관련 링크
연구자 키워드
관련분야 연구자보기
소속기관 논문보기
관련분야 논문보기
해당논문 저자보기