A low-power memristor based on 2H–MoTe2 nanosheets with synaptic plasticity and arithmetic functions. (August 2022)

• Record Type: Journal Article
• Authors: Yu, T.; Zhao, Z.; Jiang, H.; Weng, Z.; Fang, Y.; Liu, C.; Lei, W.; Shafe, S.B.; Mohtar, M.N.
• Is Part Of: Materials today nano. Volume 19(2022)
• Publication Date: 2022-08
• Subjects: Transition metal dichalcogenides -- Artificial synapse -- Cu conductive filament -- Neuromorphic computing -- Counting and adding; Nanoscience -- Periodicals; Nanotechnology -- Periodicals; Nanotechnology; Nanoscience; Nanotechnology -- Periodicals; Periodicals; Periodical; Electronic journals; Electronic journals; 620.5
• DOI: 10.1016/j.mtnano.2022.100233
• Languages: English
• ISSNs: 2588-8420

Abstract

Abstract: Bionic artificial synapses based on 2D transition metal dichalcogenides are comparable to biological synapses due to the unique properties, which are important for building brain-like computing to break the energy and data throughput limit of the von Neumann architecture. In this work, a two-terminal memristor with vertical structure was fabricated by using 2H–MoTe2 nanosheet dispersion. The fabricated memristor based on the Cu/MoTe2 /Si structure not only exhibits the stable bipolar nonvolatile resistive switching behavior but also implements the centralized distribution of threshold voltage, and the SET/RESET power can be as low as 0.86 μW/93 nW. Impressively, classical synaptic functions including long-term potentiation/long-term depression, excitatory postsynaptic currents, spike-timing-dependent plasticity, and paired-pulse facilitation were mimicked, which attribute to the formation and rupturing of Cu conductive filaments. Interestingly, the simple arithmetic functions can be operated. Therefore, this work provides a new solution for the development of synaptic devices and neural computing research in the future.