A Vertical Molecular Synaptic Transistor with Redox-Induced Analog States
We report a three-terminal, ion-gel-gated, redox-active molecular transistor that exhibits synaptic plasticity and analog conductance states. The device was composed of a ferrocene-terminated alkanethiolate self-assembled monolayer as the active channel, vertically sandwiched between a monolayer graphene source and a Au drain, and the channel conductance was modulated by an ion-gel gate. Gate voltage pulses induce an electric double layer at the ion-gel/graphene interface, triggering dynamic postsynaptic-like current responses. Our device exhibited neuroinspired plasticity, including short-term plasticity like paired-pulse facilitation and a programmable transition to long-term plasticity upon repeated stimulation. The ferrocene redox moiety was identified as the key enabler of nonvolatile switching behavior, mediating a dynamic, voltage-programmable conductance change via a synergistic mechanism of reversible redox and ion trapping. In contrast, alkanethiolate control devices without a ferrocene moiety exhibited only volatile, transient responses. We achieved multilevel conductance states with synaptic update characteristics depending on gate pulses, a crucial attribute for the learning process. As a proof of concept, a neural network simulated with our molecular synaptic transistor achieved ∼88% accuracy in MNIST pattern recognition, even after a single training epoch. These results establish vertical molecular transistor systems as promising building blocks for molecular-level neuromorphic hardware, with a three-terminal, read/write-decoupled architecture that exhibits synaptic behavior and helps overcome read-disturb of two-terminal memristive schemes.
Authors
- Takhee Lee (ORCID: https://orcid.org/0000-0001-5988-5219)
- Changjun Lee (ORCID: https://orcid.org/0000-0002-8859-9796)
- H.-S. Lee (ORCID: https://orcid.org/0009-0001-5285-4484)
- Keehoon Kang (ORCID: https://orcid.org/0000-0003-1230-3626)
- Jongwoo Nam (ORCID: https://orcid.org/0009-0009-3905-0500)
- Gunuk Wang (ORCID: https://orcid.org/0000-0001-6059-0530)
- D. Y. Kim (ORCID: https://orcid.org/0009-0007-8280-3737)
- Minwoo Song
Institutions
- Seoul National University (KR)
- Korea University (KR)
- PRG S&Tech (South Korea)
Publication Details
- Journal
- ACS Nano
- Published
- 2025-12-19
- DOI
- https://doi.org/10.1021/acsnano.5c17016
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00