A carbon-based memristor design for associative learning activities and neuromorphic computing-Reference-Cited by-同舟云学术

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A carbon-based memristor design for associative learning activities and neuromorphic computing

Published:2020 Issue:25 Volume:12 Page:13531-13539
ISSN:2040-3364
Container-title:Nanoscale
language:en
Short-container-title:Nanoscale

Author:

Pei Yifei¹²³⁴⁵,Zhou Zhenyu¹²³⁴⁵,Chen Andy Paul⁶⁷⁸⁹,Chen Jingsheng⁶⁷⁸⁹^ORCID,Yan Xiaobing¹²³⁴⁵^ORCID

Affiliation:

1. National-Local Joint Engineering Laboratory of New Energy Photovoltaic Devices

2. College of Electron and Information Engineering

3. Hebei University

4. Baoding 071002

5. P. R. of China

6. Department of Materials Science and Engineering

7. National University of Singapore

8. Singapore 117576

9. Singapore

Abstract

A model based on carbon conductive filaments (CFs) for a memristor based on carbon quantum dots (QDs) is proposed for the first time.

Funder

National Natural Science Foundation of China

Publisher

Royal Society of Chemistry (RSC)

Subject

General Materials Science

Link

http://pubs.rsc.org/en/content/articlepdf/2020/NR/D0NR02894K

Reference67 articles.

1. Electric Field Effect in Atomically Thin Carbon Films

2. Focusing on luminescent graphene quantum dots: current status and future perspectives

3. Easy synthesis of highly fluorescent carbon quantum dots from gelatin and their luminescent properties and applications

4. Recent advances in graphene quantum dots for sensing

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