AI Article Synopsis
- The study presents an InGaZnO (IGZO)-based synaptic transistor that incorporates a TiO buffer layer between the Ti electrode and IGZO channel, enhancing its synaptic functionality through a large hysteresis window.
- This synaptic transistor demonstrates significant features of synaptic plasticity, like excitatory post-synaptic current and paired-pulse facilitation, due to charge trapping and detrapping in the TiO layer.
- Simulation results show that this device can achieve a high image recognition accuracy of about 89% for handwritten digits, indicating its potential for improving neuromorphic computing systems.
Article Abstract
We demonstrate an InGaZnO (IGZO)-based synaptic transistor with a TiObuffer layer. The structure of the synaptic transistor with TiOinserted between the Ti metal electrode and an IGZO semiconductor channel Otrapping layer produces a large hysteresis window, which is crucial for achieving synaptic functionality. The Ti/TiO/IGZO synaptic transistor exhibits reliable synaptic plasticity features such as excitatory post-synaptic current, paired-pulse facilitation, and potentiation and depression, originating from the reversible charge trapping and detrapping in the TiOlayer. Finally, the pattern recognition accuracy of Modified National Institute of Standards and Technology handwritten digit images was modeled using CrossSim simulation software. The simulation results present a high image recognition accuracy of ∼89%. Therefore, this simple approach using an oxide buffer layer can aid the implementation of high-performance synaptic devices for neuromorphic computing systems.
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| http://dx.doi.org/10.1088/1361-6528/ad1540 | DOI Listing |
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