Graphene-oxide interface for optoelectronic synapse application

Ricardo Martinez-Martinez; Molla Manjurul Islam; Adithi Krishnaprasad; Tania Roy

doi:10.1038/s41598-022-09873-8

Graphene-oxide interface for optoelectronic synapse application

Sci Rep. 2022 Apr 7;12(1):5880. doi: 10.1038/s41598-022-09873-8.

Authors

Ricardo Martinez-Martinez^{1

2}, Molla Manjurul Islam^{1

3}, Adithi Krishnaprasad^{1

2}, Tania Roy^{4

5

6

7}

Affiliations

¹ NanoScience Technology Center, University of Central Florida, Orlando, FL, 32826, USA.
² Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL, 32816, USA.
³ Department of Physics, University of Central Florida, Orlando, FL, 32816, USA.
⁴ NanoScience Technology Center, University of Central Florida, Orlando, FL, 32826, USA. tania.roy@ucf.edu.
⁵ Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL, 32816, USA. tania.roy@ucf.edu.
⁶ Department of Physics, University of Central Florida, Orlando, FL, 32816, USA. tania.roy@ucf.edu.
⁷ Department of Materials Science and Engineering, University of Central Florida, Orlando, FL, 32816, USA. tania.roy@ucf.edu.

Abstract

Optoelectronic synapses combine the functionalities of a non-volatile memory and photodetection in the same device, paving the path for the realization of artificial retina systems which can capture, pre-process, and identify images on the same platform. Graphene/Ta₂O₅/graphene phototransistor exhibits synapse characteristics when visible electromagnetic radiation of wavelength 405 nm illuminates the device. The photocurrent is retained after light withdrawal when positive gate voltage is applied to the device. The device exhibits distinct conductance states, modulated by different parameters of incident light, such as pulse width and number of pulses. The conductance state can be retained for 10⁴ s, indicating long term potentiation (LTP), similar to biological synapses. By using optical and electrical pulses, the device shows optical potentiation and electrical LTD repeatably, implying their applicability in neural networks for pattern recognition.

Publication types

Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

Graphite*
Long-Term Potentiation
Neural Networks, Computer
Oxides
Synapses

Substances

Oxides
Graphite