Improvement of Conductance Modulation Linearity in a Cu2+-Doped KNbO3 Memristor through the Increase of the Number of Oxygen Vacancies
- Authors
- Park, Sung-Mean; Hwang, Hyun-Gyu; Woo, Jong-Un; Lee, Woong-Hee; Chae, Seok-June; Nahm, Sahn
- Issue Date
- 8-Jan-2020
- Publisher
- AMER CHEMICAL SOC
- Keywords
- conductance modulation linearity; neuromorphic device; artificial synapse; copper ions doping; oxygen vacancy filaments; potassium niobate memristors
- Citation
- ACS APPLIED MATERIALS & INTERFACES, v.12, no.1, pp.1069 - 1077
- Indexed
- SCIE
SCOPUS
- Journal Title
- ACS APPLIED MATERIALS & INTERFACES
- Volume
- 12
- Number
- 1
- Start Page
- 1069
- End Page
- 1077
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/58329
- DOI
- 10.1021/acsami.9b18794
- ISSN
- 1944-8244
- Abstract
- The Pt/KNbO3/TiN/Si (KN) memristor exhibits various biological synaptic properties. However, it also displays nonlinear conductance modulation with the application of identical pulses, indicating that it should be improved for neuromorphic applications. The abrupt change of the conductance originates from the inhomogeneous growth/dissolution of oxygen vacancy filaments in the KN film. The change of the filaments in a KN film is controlled by two mechanisms with different growth/dissolution rates: a redox process with a fast rate and an oxygen vacancy diffusion process with a slow rate. Therefore, the conductance modulation linearity can be improved if the growth/dissolution of the filaments is controlled by only one mechanism. When the number of oxygen vacancies in the KN film was increased through doping of Cu2+ ions, the growth/dissolution of the filaments in the Cu2+-doped KN (CKN) film was mainly influenced by the redox process of oxygen vacancies. Therefore, the CKN film exhibited improved conductance modulation linearity, confirming that the linearity of conductance modulation can be improved by increasing the number of oxygen vacancies in the memristor. This method can be applied to other memristors to improve the linearity of conductance modulation. The CKN memristor also provides excellent biological synaptic characteristics for neuromorphic computing systems.
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Collections - College of Engineering > Department of Materials Science and Engineering > 1. Journal Articles
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