Proton-Assisted Redox-Based Three-Terminal Memristor for Synaptic Device Applications
Source abstract
Abstract
Emerging technologies, i.e., spintronics, 2D materials, and memristive devices, have been widely investigated as the building block of neuromorphic computing systems. Three-terminal memristor (3TM) is specifically designed to mitigate the challenges encountered by its two-terminal counterpart as it can concurrently execute signal transmission and memory operations. In this work, we present a complementary metal-oxide-semiconductor-compatible 3TM with highly linear weight update characteristics and a dynamic range of ∼15. The switching mechanism is governed by the migration of oxygen ions and protons in and out of the channel under an external gate electric field. The involvement of the protonic defects in the electrochemical reactions is proposed based on the bipolar pulse trains required to initiate the oxidation process and the device electrical characteristics under different humidity levels. For the synaptic operation, an excellent endurance performance with over 256k synaptic weight updates was demonstrated while maintaining a stable dynamic range. Additionally, the synaptic performance of the 3TM is simulated and implemented into a four-layer neural network (NN) model, achieving an accuracy of ∼92% in MNIST handwritten digit recognition. With such desirable conductance modulation characteristics, our proposed 3T-memristor is a promising synaptic device candidate to realize the hardware implementation of the artificial NN.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Advanced Memory and Neural Computing · Photoreceptor and optogenetics research · Transition Metal Oxide Nanomaterials
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore 637371, Singapore
Funding
RIE2020 ASTAR AME IAF-ICP Grant
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