Quantum Dot‐Enhanced Dual‐Modality Heterojunction Optoelectronic Synapse for Neuromorphic Computing

Abstract The advancement of optoelectronic sensing synapse devices, which integrate multiple sensory modalities and achieve the efficiency of biological vision systems, is crucial for the field of artificial vision systems. This work incorporates CdSe/CdSe x S 1‐x quantum dots with In 2 O 3 semiconductor into a heterojunction via low‐cost fully solution‐based process to endow the synaptic transistor with dual‐modality of lights and electricity. Optoelectronic synaptic transistors exhibit sensitivity to a broad spectrum of light, encompassing wavelengths ranging from 395 to 808 nm, in addition to their responsiveness to electrical signals. The efficiency of information processing is therefore improved by integration of senses. Additionally, by doping lithium ions into the dielectric layer, the gate capacitance is increased by over ten times and significantly improved the devices channel modulation and retention characteristics. An artificial visual perception demo based on the Quantum Dot‐Enhanced synaptic ransistors (QDET) is well presented to showcase their practical application in pattern recognition and QDETs offer a promising platform for energy‐efficient, high‐performance neuromorphic systems.

Authors

Institutions

Publication Details

Journal
Advanced Optical Materials
Published
2025-02-28
DOI
https://doi.org/10.1002/adom.202403474
Citations
9
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
6.57

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Quantum Dot‐Enhanced Dual‐Modality Heterojunction Optoelectronic Synapse for Neuromorphic Computing

Lei Hao, Xin Cheng Tu, Chun Zhi Zhao, Kanghong Wang et al.
9 citations
Advanced Optical Materials
Advanced Memory and Neural Computing
6.57
article

Quantum Dot‐Enhanced Dual‐Modality Heterojunction Optoelectronic Synapse for Neuromorphic Computing

Lei Hao, Xin Cheng Tu, Chun Zhi Zhao, Kanghong Wang, Xianyao Li, Junyan Li, Sang Lam, Zhuo Chen
article en
9 citations

Abstract

Abstract The advancement of optoelectronic sensing synapse devices, which integrate multiple sensory modalities and achieve the efficiency of biological vision systems, is crucial for the field of artificial vision systems. This work incorporates CdSe/CdSe x S 1‐x quantum dots with In 2 O 3 semiconductor into a heterojunction via low‐cost fully solution‐based process to endow the synaptic transistor with dual‐modality of lights and electricity. Optoelectronic synaptic transistors exhibit sensitivity to a broad spectrum of light, encompassing wavelengths ranging from 395 to 808 nm, in addition to their responsiveness to electrical signals. The efficiency of information processing is therefore improved by integration of senses. Additionally, by doping lithium ions into the dielectric layer, the gate capacitance is increased by over ten times and significantly improved the devices channel modulation and retention characteristics. An artificial visual perception demo based on the Quantum Dot‐Enhanced synaptic ransistors (QDET) is well presented to showcase their practical application in pattern recognition and QDETs offer a promising platform for energy‐efficient, high‐performance neuromorphic systems.

Advanced Optical MaterialsVol. 13(13)
University of Liverpool (GB), Suzhou University of Science and Technology (CN), Xi’an Jiaotong-Liverpool University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 3%
Advanced Memory and Neural Computing
6.57
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.