Resonant Tunnelling Diode – Photodetectors for Spiking Neural Networks

Lourenco, J., Al-Taai, Q. R. A. , Wasige, E. and Figueiredo, J. (2022) Resonant Tunnelling Diode – Photodetectors for Spiking Neural Networks. In: 5th International Conference on Application of Optics and Photonics (AOP2022), Guimarães, Portugal, 18-22 July 2022, (doi: 10.1088/1742-6596/2407/1/012047)

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Abstract

Spike-based neuromorphic devices promise to alleviate the energy greed of the artificial intelligence hardware by using spiking neural networks (SNNs), which employ neuron like units to process information through the timing of the spikes. These neuron-like devices only consume energy when active. Recent works have shown that resonant tunnelling diodes (RTDs) incorporating optoelectronic functionalities such as photodetection and light emission can play a major role on photonic SNNs. RTDs are devices that display an N-shaped current-voltage characteristics capable of providing negative differential conductance (NDC) over a range of the operating voltages. Specifically, RTD photodetectors (RTD-PDs) show promise due to their unique mixture of the structural simplicity while simultaneously providing highly complex non-linear behavior. The goal of this work is to present a systematic study of the how the thickness of the RTD-PD light absorption layers (100, 250, 500 nm) and the device size impacts on the performance of InGaAs RTD-PDs, namely on its responsivity and time response when operating in the third (1550 nm) optical transmission window. Our focus is on the overall characterization of the device optoelectronic response including the impact of the light absorption on the device static current-voltage characteristic, the responsivity and the photodetection time response. For the static characterization, the devices I-V curves were measured under dark conditions and under illumination, giving insights on the light induced I-V tunability effect. The RTD-PD responsivity was compared to the response of a commercial photodetector. The characterization of the temporal response included its capacity to generate optical induced neuronal-like electrical spike, that is, when working as an opto-to-electrical spike converter. The experimental data obtained at each characterization phase is being used for the evaluation and refinement of a behavioral model for RTD-PD devices under construction.

Item Type:Conference Proceedings
Additional Information:EC Grant No. 828841 659 ChipAI-H2020-FETOPEN-2018–2020, FCT Grant PD/BD/142830/2018, JWNC nanofabrication centre (UGLA).
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Wasige, Professor Edward and Al-Taai, Dr Qusay
Authors: Lourenco, J., Al-Taai, Q. R. A., Wasige, E., and Figueiredo, J.
College/School:College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering
ISSN:1742-6596
Copyright Holders:Copyright © The Author(s) 2022
First Published:First published in Journal of Physics: Conference Series 2407:012047
Publisher Policy:Reproduced under a Creative Commons license
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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
303977ChipAIEdward WasigeEuropean Commission (EC)828841ENG - Electronics & Nanoscale Engineering