13–17 Sept 2021 Virtual Conference
Virtual
Europe/Vienna timezone
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Gate-control of the thermoelectric figure of merit in nanowire electric double layer transistors

16 Sept 2021, 14:40
20m
Room 3

Room 3

Oral Presentation A3. Nanowires and nanotubes: From growth phenomena to devices A3_Nanowires and nanotubes: From growth phenomena to devices

Speaker

Francesco Rossella (NEST, Scuola Normale Superiore and Istituto Nanoscienze-CNR)

Description

Thermoelectric properties of semiconductors – the ideal materials for thermoelectrics due to their advantageous electro/thermal transport properties – are rather fixed in standard devices, and little to no room is available for modulation of parameters influencing the thermoelectric figure of merit ZT=σS^2 T/κ, where σ is the electrical conductivity, S is the Seebeck coefficient, κ is the thermal conductivity and T is the temperature.
In this work, we aim at the dynamical tuning of the thermoelectric properties of semiconducting nanowires by exploiting the outstanding performance of electrolytes as gate dielectrics. By exploiting ionic liquids – a class of highly flexible and promising electrolytes – we develop devices based on highly doped semiconducting nanowires that are able to simultaneously access the thermal conduction properties of the material and to modulate the electrical conduction properties. The chosen ionic liquid used in this work acts as a thermal insulator with respect to heat conduction in the nanostructure, allowing to directly measure thermal conductivity via the fully-electrical 3ω technique [1], while taking advantage of the electrolyte as gate dielectric to implement outperforming field effect control over the electrical conductivity [2,3]. Ultimately, our findings show that the developed platform allows to probe and dynamically optimize the thermoelectric figure of merit by exploiting field effect-induced modulation of the electrical properties of the nanostructure in a liquid electrolyte environment [4].

References:

[1] M. Rocci, et al., J. Mater. Eng. Perform. 27, 12 (2018).
[2] J. Lieb, et al., Adv. Funct. Mater. 29, 3 (2019)
[3] D. Prete, et al., AIP Conf. Proc. 2145 (2019)
[4] D. Prete, et al., in preparation

Speaker Country Italy

Authors

Mr Domenic Prete (NEST, Scuola Normale Superiore and Istituto Nanoscienze-CNR) Dr Elisabetta Di Maggio (Università di Pisa, Dipartimento di Ingegneria dell’Informazione) Dr Valentina Zannier (NEST, Scuola Normale Superiore and Istituto Nanoscienze-CNR) Maria Jesus Rodriguez-Douton (NEST, Scuola Normale Superiore and Istituto Nanoscienze-CNR) Prof. Lorenzo Guazzelli (Università di Pisa, Dipartimento di Farmacia) Prof. Fabio Beltram (NEST, Scuola Normale Superiore and Istituto Nanoscienze-CNR) Prof. Lucia Sorba (NEST, Scuola Normale Superiore and Istituto Nanoscienze-CNR) Prof. Giovanni Pennelli (Università di Pisa, Dipartimento di Ingegneria dell’Informazione) Francesco Rossella (NEST, Scuola Normale Superiore and Istituto Nanoscienze-CNR)

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