ZnO-based resistive memory with self-rectifying behavior for neuromorphic devices-Reference-Cited by-同舟云学术

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ZnO-based resistive memory with self-rectifying behavior for neuromorphic devices

Published:2024-10 Issue: Volume:671 Page:160749
ISSN:0169-4332
Container-title:Applied Surface Science
language:en
Short-container-title:Applied Surface Science

Author:

Na Hyesung^ORCID,So Hyojin^ORCID,Jang Heesung^ORCID,Park Jihee^ORCID,Kim Sungjun^ORCID

Funder

NRF

Publisher

Elsevier BV

Reference77 articles.

1. Threshold-variation-tolerant coupling-gate α-IGZO synaptic transistor for more reliably controllable hardware neuromorphic system;Kang;IEEE Access,2021

2. Linear and Symmetric Weight Update of CuOx/HfOx/WOxECRAM Synapse for Neuromorphic Systems;Kang,2022

3. Impact of HfO2 dielectric layer placement in Hf0.5Zr0.5O2-based ferroelectric tunnel junctions for neuromorphic applications;Kim;Adv. Mater. Technol.,2024

4. Highly uniform resistive switching characteristics of Ti/TaOx/ITO memristor devices for neuromorphic system;Ju;J. Alloy. Compd.,2023

5. Multi-state MRAM cells for hardware neuromorphic computing;Rzeszut;Sci. Rep.,2022

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