Multicolor Optoelectronic Synapse Enabled by Photon‐Modulated Remote Doping in Solution‐Processed Van Der Waals Heterostructures
Year: 2025
Type: article
Abstract: Optoelectronic synapses have attracted considerable attention for emulating biological visual perception by enabling the recognition of complex visual stimuli, including spatial patterns and multicolor information. Despite significant progress, the realization of multicolor classification with simple and scalable device architecture remains a fundamental challenge, requiring strategies that overcome the limitations of conventional device configurations. Here, a scalable van der Waals heterostructure device is presented that enables multicolor optoelectronic processing by vertically integrating solution‐processed molybdenum disulfide (MoS 2 ) as a light‐absorbing layer and single‐walled carbon nanotubes (SWCNTs) as a semiconducting channel. Unlike conventional complex architectures, such as serially connected synaptic devices and optical‐sensors, the approach employs an electronically disconnected but interactive MoS 2 layer to facilitate photon‐modulated carrier doping in the adjacent SWCNTs channel. This configuration enables bi‐directional photocurrent behavior under different wavelength illumination, essential for emulating the retina's chromatic adaptation while maintaining a structurally simple and scalable design. Leveraging this unique bi‐directional photoresponse, an optical neural network framework is integrated that independently processes distinct spectral information, enabling highly efficient multicolor pattern classification. This synergistic strategy is essential for realizing scalable optoelectronic synapses, as evidenced by a classification accuracy of 92.0%, offering a promising platform for next‐generation vision systems.
Source: Advanced Functional Materials
Authors: Jihyun Kim, Hyunbin Kim, Gang Jin Cheon, Dohyun Lee, In Soo Kim, Uiyeon Won, Jongseok Lee, Sang Min Won, Joohoon Kang
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $5,790
Awards: G4102960863, G471049413, G6223488664
OpenAlex ID: W4415673837
