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

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 microscopy, and X‐ray diffraction confirm the MD‑predicted ion dynamic transition at 8:1 EO ratio and identify phase crystallization at the ultrahigh 2:1 ratio. Consequently, Li‐EGTs fabricated with the optimized 2:1 EO ratio successfully achieve an accuracy of 89.51% in neural network training. This study bridges atomic‑scale insights and device performance, offering a systematic, precision‑engineered framework for complex spatiotemporal ion dynamics in artificial synaptic EGTs.

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Publication Details

Journal
Advanced Functional Materials
Published
2025-11-12
DOI
https://doi.org/10.1002/adfm.202517100
Primary Topic
Advanced Memory and Neural Computing
Type
article
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article

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

Yeonseo Kim, Haeyeon Lee, Tengfei Luo, Sobin Alosious et al.
Advanced Functional Materials
Advanced Memory and Neural Computing
article

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

Yeonseo Kim, Haeyeon Lee, Tengfei Luo, Sobin Alosious, Minho Jin
article en

Abstract

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 microscopy, and X‐ray diffraction confirm the MD‑predicted ion dynamic transition at 8:1 EO ratio and identify phase crystallization at the ultrahigh 2:1 ratio. Consequently, Li‐EGTs fabricated with the optimized 2:1 EO ratio successfully achieve an accuracy of 89.51% in neural network training. This study bridges atomic‑scale insights and device performance, offering a systematic, precision‑engineered framework for complex spatiotemporal ion dynamics in artificial synaptic EGTs.

Advanced Functional MaterialsVol. 36(24)
University of Notre Dame (US), Seoul National University of Science and Technology (KR), Seoul National University (KR)
Openalex Percentile: Top 66%
Advanced Memory and Neural Computing
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Tunable Linear Weight Modulation via Ion Dynamics in Electrolyte‐Gated Synaptic Transistors: Molecular Dynamics and Experimental Insights into Ion Concentration Effects — Yeonseo Kim, Haeyeon Lee, et al. · Advanced Functional Materials (2025) | TGRS Research Map | TGRS