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Genetic-based optimization of a multi insulator tunneling diode for THz energy harvesting

Published online by Cambridge University Press:  17 March 2020

Mazen Shanawani*
Affiliation:
Department of Electrical, Electronic and Information Engineering, Edificio Storico, via. del Risorgimento 2, 40136, Bologna, Italy
Diego Masotti
Affiliation:
Department of Electrical, Electronic and Information Engineering, Edificio Storico, via. del Risorgimento 2, 40136, Bologna, Italy
Alessandra Costanzo
Affiliation:
Department of Electrical, Electronic and Information Engineering, Edificio Storico, via. del Risorgimento 2, 40136, Bologna, Italy
*
Author for correspondence: Mazen Shanawani, E-mail: mazen.shanawani@unibo.it

Abstract

The deployment of multi-insulator tunneling diodes has recently had more attention to be used as rectifiers in energy harvesting rectennas with good potentiality for a millimeter and terahertz range. However, with the rather complicated math to obtain the current–voltage relation, it is difficult to evaluate the design figures of merit (FOM)s such as asymmetry, nonlinearity, responsivity, and dynamic resistance and monitor the impact of changing physical parameters on them. This complicates the decision-making process for the required physical parameters. In this work, a heuristic optimization framework using genetic algorithm is suggested using the transfer matrix method to find the combination of physical parameters which satisfies the minimum required FOM set by users and weighted by their preference.

Type
Research Article
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

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