Surface Modification of a Titanium Carbide MXene Memristor to Enhance Memory Window and Low-Power Operation
- Authors
- Mullani, N.B.; Kumbhar, D.D.; Lee, D.-H.; Kwon, M.J.; Cho, S.-Y.; Oh, N.; Kim, E.-T.; Dongale, T.D.; Nam, S.Y.; Park, J.H.
- Issue Date
- Jun-2023
- Publisher
- John Wiley and Sons Inc
- Keywords
- artificial synapses; memory window engineering; MXenes; resistive switchings; spike-timing-dependent plasticity
- Citation
- Advanced Functional Materials, v.33, no.26
- Indexed
- SCIE
SCOPUS
- Journal Title
- Advanced Functional Materials
- Volume
- 33
- Number
- 26
- URI
- https://scholarworks.gnu.ac.kr/handle/sw.gnu/30842
- DOI
- 10.1002/adfm.202300343
- ISSN
- 1616-301X
1616-3028
- Abstract
- With the demand for low-power-operating artificial intelligence systems, bio-inspired memristor devices exhibit potential in terms of high-density memory functions and the emulation of the synaptic dynamics of the human brain. The 2D material MXene attracts considerable interest for use in resistive-switching memory and artificial synapse devices owing to its excellent physicochemical properties in memristor devices. However, few memristive and synaptic MXene devices that display increased switching performances are reported, with no significant results. Herein, the conductivity of MXene (Ti3C2Tx) is engineered via etching and oxidation to enhance the switching performance of the device. The exceptional properties of partially oxidized MXene memristors include large memory windows and low threshold biases, and the complex spike-timing-dependent plasticity synaptic rules are also emulated. The low threshold potential distribution, reliable retention time (104 s), and distinct resistance states with a high ON–OFF ratio (>104) are the main memory-related features of this device. The experimentally determined switching potentials of the optimized device are also uniformly distributed, according to a statistical probability-based approach. This investigation may promote the essential material properties for use in high-density non-volatile memory storage and artificial synapse systems in the field of innovative nanoelectronic devices. © 2023 Wiley-VCH GmbH.
- Files in This Item
- There are no files associated with this item.
- Appears in
Collections - 공학계열 > Dept.of Materials Engineering and Convergence Technology > Journal Articles

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.