The coexistence of threshold and memory switching characteristics of ALD HfO2 memristor synaptic arrays for energy-efficient neuromorphic computing-Reference-Cited by-同舟云学术

The coexistence of threshold and memory switching characteristics of ALD HfO2 memristor synaptic arrays for energy-efficient neuromorphic computing

Published:2020 Issue:26 Volume:12 Page:14120-14134
ISSN:2040-3364
Container-title:Nanoscale
language:en
Short-container-title:Nanoscale

Author:

Abbas Haider¹²³⁴^ORCID,Abbas Yawar⁵⁶⁷⁸^ORCID,Hassan Gul⁹¹⁰¹¹¹²,Sokolov Andrey Sergeevich¹²³⁴^ORCID,Jeon Yu-Rim¹²³⁴,Ku Boncheol¹²³⁴,Kang Chi Jung⁵¹³¹⁴⁴,Choi Changhwan¹²³⁴^ORCID

Affiliation:

1. Division of Materials Science and Engineering

2. Hanyang University

3. Seoul 04763

4. Republic of Korea

5. Department of Physics

6. Khalifa University

7. Abu Dhabi 127788

8. United Arab Emirates

9. Centre for Advanced Electronics & Photovoltaic Engineering

10. International Islamic University

11. Islamabad 44000

12. Pakistan

13. Myongji University

14. Gyeonggi-do 17058

Abstract

Coexistence of threshold and memory switching characteristics of ALD HfO₂ memristor synaptic arrays for energy-efficient neuromorphic computing.

Funder

National Research Foundation of Korea

Publisher

Royal Society of Chemistry (RSC)

Subject

General Materials Science

Link

http://pubs.rsc.org/en/content/articlepdf/2020/NR/D0NR02335C

Reference39 articles.

1. Edge Computing for the Internet of Things: A Case Study

2. Fog-Based Crime-Assistance in Smart IoT Transportation System

3. Review of memristor devices in neuromorphic computing: materials sciences and device challenges

4. Overview of emerging nonvolatile memory technologies

5. Tailored nanoplateau and nanochannel structures using solution-processed rutile TiO2 thin films for complementary and bipolar switching characteristics

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