Evidence map›Paper›PMID 37382679›Full record

ReviewDiscover nano2023

Resistive random access memory: introduction to device mechanism, materials and application to neuromorphic computing.

Furqan Zahoor, Fawnizu Azmadi Hussin, Usman Bature Isyaku, Shagun Gupta, Farooq Ahmad Khanday, Anupam Chattopadhyay, Haider Abbas

Abstract readReview
In one paragraph

Review in Discover nano, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
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.

Furqan ZahoorSchool of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore.
Fawnizu Azmadi HussinDepartment of Electrical and Electronics Engineering, Universiti Teknologi Petronas, Seri Iskandar, Malaysia. fawnizu@utp.edu.my.
Usman Bature IsyakuDepartment of Electrical and Electronics Engineering, Universiti Teknologi Petronas, Seri Iskandar, Malaysia.
Shagun GuptaSchool of Electronics and Communication Engineering, Shri Mata Vaishno Devi University, Katra, India.
Farooq Ahmad KhandayDepartment of Electronics & Instrumentation Technology, University of Kashmir, Srinagar, India.
Anupam ChattopadhyaySchool of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore.
Haider AbbasDivision of Material Science and Engineering, Hanyang University, Seoul, South Korea.

Funding

Nanyang Technological University NRF-CRP21-2018-0003Yayasan UTP 015LCO-245
6 · The paper itself

Abstract

The modern-day computing technologies are continuously undergoing a rapid changing landscape; thus, the demands of new memory types are growing that will be fast, energy efficient and durable. The limited scaling capabilities of the conventional memory technologies are pushing the limits of data-intense applications beyond the scope of silicon-based complementary metal oxide semiconductors (CMOS). Resistive random access memory (RRAM) is one of the most suitable emerging memory technologies candidates that have demonstrated potential to replace state-of-the-art integrated electronic devices for advanced computing and digital and analog circuit applications including neuromorphic networks. RRAM has grown in prominence in the recent years due to its simple structure, long retention, high operating speed, ultra-low-power operation capabilities, ability to scale to lower dimensions without affecting the device performance and the possibility of three-dimensional integration for high-density applications. Over the past few years, research has shown RRAM as one of the most suitable candidates for designing efficient, intelligent and secure computing system in the post-CMOS era. In this manuscript, the journey and the device engineering of RRAM with a special focus on the resistive switching mechanism are detailed. This review also focuses on the RRAM based on two-dimensional (2D) materials, as 2D materials offer unique electrical, chemical, mechanical and physical properties owing to their ultrathin, flexible and multilayer structure. Finally, the applications of RRAM in the field of neuromorphic computing are presented.

Indexed as

2D materialsEmerging memory technologiesHigh-density memoryNeuromorphic computingPower dissipationResistive random access memory (RRAM)

Identifiers

PMID37382679
PMCPMC10409712

What OpenQuestion holds

Textmetadata
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.