Evidence map›Paper›PMID 41861102›Full record

ReviewAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2026

Advances and Perspectives in Graphene-Based Quantum Dots Enabled Neuromorphic Devices.

Yulin Zhen, Wei Zeng, Zherui Zhao, JiYu Zhao, Ziyan Huang, Zhuo Chen, Kui Zhou, Guanglong Ding, Su-Ting Han, Ye Zhou

Abstract readReview
In one paragraph

Review in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Yulin ZhenInstitute For Advanced Study, Shenzhen University, Shenzhen, P. R. China.
Wei ZengInstitute For Advanced Study, Shenzhen University, Shenzhen, P. R. China.
Zherui ZhaoInstitute For Advanced Study, Shenzhen University, Shenzhen, P. R. China.
JiYu ZhaoInstitute For Advanced Study, Shenzhen University, Shenzhen, P. R. China.
Ziyan HuangInstitute For Advanced Study, Shenzhen University, Shenzhen, P. R. China.
Zhuo ChenInstitute For Advanced Study, Shenzhen University, Shenzhen, P. R. China.
Kui ZhouInstitute For Advanced Study, Shenzhen University, Shenzhen, P. R. China.
Guanglong DingState Key Laboratory of Radio Frequency Heterogeneous Integration, Shenzhen University, Shenzhen, P. R. China.
Su-Ting HanDepartment of Applied Biology and Chemical Technology, The Hong Kong Polytechnic University, Kowloon, Hong Kong, P. R. China.
Ye ZhouInstitute For Advanced Study, Shenzhen University, Shenzhen, P. R. China.ORCID https://orcid.org/0000-0002-0273-007X

Funding

Department of Education of Guangdong Province 2025ZDZX3024Guangdong Basic and Applied Basic Research Foundation 2024A1515011737Guangdong Basic and Applied Basic Research Foundation 2024B1515040002National Natural Science Foundation of China 62304137Research Institute for Smart Energy U-CDC9Science, Technology and Innovation Commission of Shenzhen Municipality JCYJ20250604181254072State Key Laboratory of Radio Frequency Heterogeneous Integration 2024010Young Collaborative Research Grant C5001-24
6 · The paper itself

Abstract

With the rapid rise in demand for artificial intelligence and brain-inspired computing, traditional von Neumann architecture is gradually approaching physical limitations in terms of computing power density, energy efficiency, and real-time performance. Graphene quantum dots (GQDs) and graphene oxide quantum dots (GOQDs), as zero-dimensional carbon-based materials with quantum confinement effects and tunable band structures, have shown significant potential in building next-generation ultra-low-power, large-scale integrated neuromorphic devices. This review systematically summarizes the main preparation strategies of graphene-based QDs and their structural regulation and functionalization methods. It focuses on the core functions of graphene-based QDs in synaptic working mechanisms such as charge capture, ion migration, and optoelectronic cooperation, as well as their latest progress in non-volatile memories, electrical and optoelectronic artificial synapses, and neuromorphic systems. Finally, this review article summarizes the current key challenges from the perspectives of material controllability, mechanism interpretability, device structural engineering, and system-level heterogeneous integration, and proposes future research directions to provide reference for the development of next-generation high-efficiency, scalable brain-inspired computing hardware.

Indexed as

artificial synapsesbrain‐inspired computinggraphene‐based quantum dotsneuromorphic devicesnon‐volatile memories

Identifiers

PMID41861102
PMCPMC13326020

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.