Evidence map›Paper›PMID 36872944›Full record

ReviewScience and technology of advanced materials2023

A review of memristor: material and structure design, device performance, applications and prospects.

Yongyue Xiao, Bei Jiang, Zihao Zhang, Shanwu Ke, Yaoyao Jin, Xin Wen, Cong Ye

Abstract readReview
In one paragraph

Review in Science and technology of advanced materials, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing 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

38 citing papers in PubMed.

  1. Article
  2. Effects of Gamma Irradiation on the Artificial Spiking Neurons Based on NbOSmall (Weinheim an der Bergstrasse, Germany) · 2026
    Article
  3. Review
  4. Article
  5. Article
  6. HfOScience advances · 2026
    Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Review
  12. Review
  13. Article
  14. Article
  15. VOAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Article
  16. Article
  17. Review
  18. Review
  19. Electric Field-Driven Conformational Changes in Molecular Memristor and Synaptic Behavior.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Article
  20. 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

7 authors.

Yongyue XiaoHubei Key Laboratory of Ferro-& Piezoelectric Materials and Devices, Faculty of Physics and Electronic Science, Hubei University, Wuhan, China.
Bei JiangHubei Key Laboratory of Ferro-& Piezoelectric Materials and Devices, Faculty of Physics and Electronic Science, Hubei University, Wuhan, China.
Zihao ZhangHubei Key Laboratory of Ferro-& Piezoelectric Materials and Devices, Faculty of Physics and Electronic Science, Hubei University, Wuhan, China.
Shanwu KeHubei Key Laboratory of Ferro-& Piezoelectric Materials and Devices, Faculty of Physics and Electronic Science, Hubei University, Wuhan, China.
Yaoyao JinHubei Key Laboratory of Ferro-& Piezoelectric Materials and Devices, Faculty of Physics and Electronic Science, Hubei University, Wuhan, China.
Xin WenFaculty of Chemical Technology and Engineering, West Pomeranian University of Technology in Szczecin, Szczecin, Poland.
Cong YeHubei Key Laboratory of Ferro-& Piezoelectric Materials and Devices, Faculty of Physics and Electronic Science, Hubei University, Wuhan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the booming growth of artificial intelligence (AI), the traditional von Neumann computing architecture based on complementary metal oxide semiconductor devices are facing memory wall and power wall. Memristor based in-memory computing can potentially overcome the current bottleneck of computer and achieve hardware breakthrough. In this review, the recent progress of memory devices in material and structure design, device performance and applications are summarized. Various resistive switching materials, including electrodes, binary oxides, perovskites, organics, and two-dimensional materials, are presented and their role in the memristor are discussed. Subsequently, the construction of shaped electrodes, the design of functional layer and other factors influencing the device performance are analyzed. We focus on the modulation of the resistances and the effective methods to enhance the performance. Furthermore, synaptic plasticity, optical-electrical properties, the fashionable applications in logic operation and analog calculation are introduced. Finally, some critical issues such as the resistive switching mechanism, multi-sensory fusion, system-level optimization are discussed.

Indexed as

Artificial intelligencedevice performancein-memory computingmaterial and structure designmemristor

Identifiers

PMID36872944
PMCPMC9980037

What OpenQuestion holds

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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.