Evidence map›Paper›PMID 40264852›Full record

ReviewCyborg and bionic systems (Washington, D.C.)2025

Neuromorphic Floating-Gate Memory Based on 2D Materials.

Chao Hu, Lijuan Liang, Jinran Yu, Liuqi Cheng, Nianjie Zhang, Yifei Wang, Yichen Wei, Yixuan Fu, Zhong Lin Wang, Qijun Sun

Abstract readReview
In one paragraph

Review in Cyborg and bionic systems (Washington, D.C.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Two-Dimensional Flash Memory: Materials, Interfaces, and Storage-Computing Convergence.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  2. Review
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.

Chao HuSchool of Printing and Packaging Engineering, Beijing Institute of Graphic Communication, Beijing 102627, P. R. China.
Lijuan LiangSchool of Printing and Packaging Engineering, Beijing Institute of Graphic Communication, Beijing 102627, P. R. China.
Jinran YuBeijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 101400, P. R. China.
Liuqi ChengBeijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 101400, P. R. China.
Nianjie ZhangSchool of Printing and Packaging Engineering, Beijing Institute of Graphic Communication, Beijing 102627, P. R. China.
Yifei WangBeijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 101400, P. R. China.
Yichen WeiBeijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 101400, P. R. China.
Yixuan FuSchool of Printing and Packaging Engineering, Beijing Institute of Graphic Communication, Beijing 102627, P. R. China.
Zhong Lin WangBeijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 101400, P. R. China.
Qijun SunBeijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 101400, P. R. China.ORCID https://orcid.org/0000-0003-2130-7389

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent years, the rapid progression of artificial intelligence and the Internet of Things has led to a significant increase in the demand for advanced computing capabilities and more robust data storage solutions. In light of these challenges, neuromorphic computing, inspired by human brain's architecture and operation principle, has surfaced as a promising answer to the growing technological demands. This novel methodology emulates the biological synaptic mechanisms for information processing, enabling efficient data transmission and computation at the identical position. Two-dimensional (2D) materials, distinguished by their atomic thickness and tunable physical properties, exhibit substantial potential in emulating synaptic plasticity and find broad applications in neuromorphic computing. With respect to device architecture, memory devices based on floating-gate (FG) structures demonstrate robust data retention capabilities and have been widely used in the realm of flash memory. This review begins with a succinct introduction to 2D materials and FG transistors, followed by an in-depth discussion on remarkable research progress in the integration of 2D materials with FG transistors for applications in neuromorphic computing and memory. This paper offers a thorough review of the existing research landscape, encapsulating the notable progress in swiftly expanding field. In conclusion, it addresses the constraints encountered by FG transistors using 2D materials and delineates potential future trajectories for investigation and innovation within this area.

Identifiers

PMID40264852
PMCPMC12012298

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.