Superionic Silver Halide Solid Electrolyte: Dielectric Property and Iontronic Memtransistor Application for Bioinspired Computingopen access
- Authors
- Mukherjee, Arka; Mohanan, Kannan Udaya; Sagar, Srikrishna; Das, Bikas C.
- Issue Date
- Jan-2024
- Publisher
- WILEY-V C H VERLAG GMBH
- Keywords
- iontronics; negative differential transconductance; neuromorphic computing; pattern recognition; rubidium silver iodide; synaptic weight
- Citation
- ADVANCED FUNCTIONAL MATERIALS, v.34, no.1
- Journal Title
- ADVANCED FUNCTIONAL MATERIALS
- Volume
- 34
- Number
- 1
- URI
- https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/90417
- DOI
- 10.1002/adfm.202304228
- ISSN
- 1616-301X
1616-3028
- Abstract
- Technology like high-level parallel information processing and storage in the brain remains a dream to the researchers using conventional solid-state electronics. Here, a robust thin film bilayer superionic dielectric of poly(ethylene oxide) (PEO) and rubidium silver iodide (RbAg4I5) is developed to fabricate solid-state iontronic synaptic memtransistors, which can serve as the basic building blocks for the hardware-implementation of neuromorphic computing. X-ray photoelectron spectroscopy and impedance measurements precisely confirm the stoichiometric composition of RbAg4I5 and dielectric nature combining with a PEO layer, respectively. The superionic bilayer PEO/RbAg4I5 gating effectively modulates the channel conductance analogously and displays memtransistor functionality. Interestingly, the transfer curves depict a colossal hysteresis yielding negative differential transconductance of peak-to-valley ratio up to 5 x 103 after the gate-controlled resistive switching. Systematic electrical characterizations reveal a variety of synaptic behaviors, including the inhibitory postsynaptic current, paired-pulse depression, and potentiation/depression curve. Finally, an artificial neural network for off-chip digit recognition is simulated to assess the performance of the device for the neuromorphic application and achieved a test accuracy of 95.94% on the Modified National Institute of Standards and Technology dataset. A robust solid-state iontronic synaptic memtransistor is developed using a bilayer thin-film dielectric of poly(ethylene oxide) and superionic rubidium silver iodide (RbAg4I5), which can serve as the basic building blocks for neuromorphic computing hardware-implementation. The transfer curves of this device depict a colossal hysteresis of resistive switching and yield an interesting signature of negative differential transconductance.image
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