Synaptic transistor based on reversible hydrogenation of graphene channel

Applied Physics Letters, Journal Year: 2025, Volume and Issue: 126(1)

Published: Jan. 2, 2025

Graphene transistors with a gate-controlled transition of neuromorphic functions between artificial neurons and synapses have attracted increasing attention because the atomic thickness could be easily modulated by different stimuli, which is very beneficial for synaptic applications. As modulation method, graphene electrolyte-gated transistor (EGT) has been proposed, in electrical conductance channel reversible electrochemical hydrogenation graphene. However, only sparse physically realized graphene-based H+-EGTs reported due to difficulty achieving high concentration protons at electrolyte–graphene interface. Here, we highly defective gel electrolyte [H3PO4/poly(vinyl alcohol)], based on dehydrogenation defected-graphene, performing similar as common transistors, good retention (<1% attenuation per minute), analog tunability (>200 nonvolatile states), precisely controllable resistance (∼0.4% step flipped event). In addition, cyclic voltammetry test was applied confirm channel. It expected that this principle can provide ideas designing enabling integrated in-memory computing sensing system.

Language: Английский

Ion–Electron Interactions in 2D Nanomaterials-Based Artificial Synapses for Neuromorphic Applications

ACS Nano, Journal Year: 2025, Volume and Issue: unknown

Published: April 29, 2025

With the increasing limitations of conventional computing techniques, particularly von Neumann bottleneck, brain's seamless integration memory and processing through synapses offers a valuable model for technological innovation. Inspired by biological synapse facilitating adaptive, low-power computation modulating signal transmission via ionic conduction, iontronic synaptic devices have emerged as one most promising candidates neuromorphic computing. Meanwhile, atomic-scale thickness tunable electronic properties van der Waals two-dimensional (2D) materials enable possibility designing highly integrated, energy-efficient that closely replicate plasticity. This review comprehensively analyzes advancements in based on 2D materials, focusing electron-ion interactions both transistors memristors. The challenges material stability, scalability, device are evaluated, along with potential solutions future research directions. By highlighting these developments, this insights into advancing systems.

Language: Английский