Surface-Dominated HfO<sub>2</sub> Nanorod-Based Memristor Exhibiting Highly Linear and Symmetrical Conductance Modulation for High-Precision Neuromorphic Computing-Reference-Cited by-同舟云学术

Surface-Dominated HfO₂ Nanorod-Based Memristor Exhibiting Highly Linear and Symmetrical Conductance Modulation for High-Precision Neuromorphic Computing

Published:2022-09-23 Issue:39 Volume:14 Page:44550-44560
ISSN:1944-8244
Container-title:ACS Applied Materials & Interfaces
language:en
Short-container-title:ACS Appl. Mater. Interfaces

Author:

Kwon Jae Uk¹²,Song Young Geun¹,Kim Ji Eun¹²,Chun Suk Yeop¹³,Kim Gu Hyun⁴,Noh Gichang⁵,Kwak Joon Young⁵^ORCID,Hur Sunghoon¹,Kang Chong-Yun¹³^ORCID,Jeong Doo Seok⁴,Oh Soong Ju²^ORCID,Yoon Jung Ho¹^ORCID

Affiliation:

1. Electronic Materials Research Center, Korea Institute of Science and Technology (KIST), Seoul 02791, Republic of Korea

2. Department of Materials Science and Engineering, Korea University, Seoul 02841, Republic of Korea

3. KU-KIST Graduate School of Converging Science and Technology, Korea University, Seoul 02841, Republic of Korea

4. Division of Materials Science and Engineering, Hanyang University, Seoul 04763, Republic of Korea

5. Center for Neuromorphic Engineering, Korea Institute of Science and Technology (KIST), Seoul 02791, Republic of Korea

Funder

National Research Foundation of Korea

Korea Institute of Science and Technology

Publisher

American Chemical Society (ACS)

Subject

General Materials Science

Link

https://pubs.acs.org/doi/pdf/10.1021/acsami.2c12247

Reference43 articles.

1. A fully integrated reprogrammable memristor–CMOS system for efficient multiply–accumulate operations

2. Emerging Memory Devices for Neuromorphic Computing

3. Emerging Memristive Artificial Synapses and Neurons for Energy‐Efficient Neuromorphic Computing

4. Memristive and CMOS Devices for Neuromorphic Computing

5. Nanoscale Memristor Device as Synapse in Neuromorphic Systems

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