SNU CBE

Tunable Linear Weight Modulation via Ion Dynamics in Electrolyte‐Gated Synaptic Transistors: Molecular Dynamics and Experimental Insights into Ion Concentration Effects

2025 · Advanced Functional Materials

저자

Haeyeon Lee, Sobin Alosious, Minho Jin, Yeonseo Kim, Yeonseo Kim, Tengfei Luo, 김연상 (Youn Sang Kim), Youn Sang Kim

연구주제

Advanced Memory and Neural Computing · Advanced Battery Materials and Technologies · Conducting polymers and applications

NTIS 과학기술표준분류

가장 가까운 분류(재료 > 고분자재료 > 전기/전자정보용 소재기술)가 화학·화공 범위 밖이다. 배정 근거: AI 키워드가 잡은 NTIS 과제의 분류.

AI 연구 키워드·방법

인공 시냅스 전해질 게이트 트랜지스터 polymer electrolyte

분자동역학 시뮬레이션

키워드 (OpenAlex)

electrolyte-gated transistors artificial synapses lithium-ion conductors poly(ethylene oxide) electrolyte ion concentration effects ionic conductivity phase crystallization conductance modulation

초록

Abstract Electrolyte‐gated transistors (EGTs) are promising candidates for low‐power and energy‐efficient artificial synapses utilizing rapid ion‐mediated electrostatic and electrochemical reactions. However, the correlation between sub‐nanosecond ion transport and linear conductance modulation remains elusive when analyzed solely by macroscopic electrical characterization. Here, molecular dynamics (MD) simulations are integrated with experiments using Li‐EGTs at different ion concentrations. MD simulations quantify Li⁺ displacement, coordination environments, and ionic conductivity in poly(ethylene oxide) electrolytes, revealing suppressed Li⁺ diffusivity and reorganization of the ethylene oxide (EO) solvation structure at an [EO]:[Li⁺] ratio of 8:1. EGTs are fabricated with different EO ratios to investigate the transition regime. Electrochemical impedance spectroscopy, optical microsc…

이 논문을 지원한 국가R&D 과제 (NTIS 성과)

NTIS 성과DB(2020–24)에서 DOI 매칭 없음

인접 그래프

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교수 1

김연상

연구주제 1

Advanced Memory and Neural Computing

키워드 2

인공 시냅스 · 전해질 게이트 트랜지스터

방법 1

분자동역학 시뮬레이션