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Emulation of synaptic functions with low voltage organic memtransistor for hardware oriented neuromorphic computing

Here, various synaptic functions and neural network simulation based pattern-recognition using novel, solution-processed organic memtransistors (memTs) with an unconventional redox-gating mechanism are demonstrated. Our synaptic memT device using conjugated polymer thin-film and redox-active solid e...

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Detalles Bibliográficos
Autores principales: Sagar, Srikrishna, Udaya Mohanan, Kannan, Cho, Seongjae, Majewski, Leszek A., Das, Bikas C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8907356/
https://www.ncbi.nlm.nih.gov/pubmed/35264605
http://dx.doi.org/10.1038/s41598-022-07505-9
Descripción
Sumario:Here, various synaptic functions and neural network simulation based pattern-recognition using novel, solution-processed organic memtransistors (memTs) with an unconventional redox-gating mechanism are demonstrated. Our synaptic memT device using conjugated polymer thin-film and redox-active solid electrolyte as the gate dielectric can be routinely operated at gate voltages (V(GS)) below − 1.5 V, subthreshold-swings (S) smaller than 120 mV/dec, and ON/OFF current ratio larger than 10(8). Large hysteresis in transfer curves depicts the signature of non-volatile resistive switching (RS) property with ON/OFF ratio as high as 10(5). In addition, our memT device also shows many synaptic functions, including the availability of many conducting-states (> 500) that are used for efficient pattern recognition using the simplest neural network simulation model with training and test accuracy higher than 90%. Overall, the presented approach opens a new and promising way to fabricate high-performance artificial synapses and their arrays for the implementation of hardware-oriented neural network.