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Title: Thermoplasmonic response of semiconductor nanoparticles: A comparison with metals
Authors: Thakore, Vaibhav
Tang, Janika
Conley, Kevin
Ala-Nissila, Tapio
Karttunen, Mikko
Issue Date: 2018
Publisher: © Wiley
Citation: THAKORE, V. ... et al., 2018. Thermoplasmonic response of semiconductor nanoparticles: A comparison with metals. Advanced Theory and Simulations, doi: 10.1002/adts.201800100
Abstract: A number of applications in nanoplasmonics utilize noble metals, gold (Au) and silver (Ag), as the materials of choice. However, these materials suffer from problems of poor thermal and chemical stability with significant dissipative losses under high-temperature conditions. In this regard, semiconductor nanoparticles have attracted attention with their promising characteristics of highly tunable plasmonic resonances, low ohmic losses, and greater thermochemical stability. Here, the size-dependent thermoplasmonic properties of semiconducting silicon and gallium arsenide nanoparticles are investigated to compare them with Au nanoparticles using Mie theory. To this end, experimentally estimated models of dielectric permittivity are employed. Among the various permittivity models for Au, the Drude–Lorentz (DL) and the Drude and critical points (DCP) models are further compared. Results show a redshift in the scattering and absorption resonances for the DL model while the DCP model presents a blueshift. A massive Drude broadening contributes strongly to the damping of resonances in Au nanoparticles at elevated temperatures. In contrast, the semiconductor nanoparticles do not exhibit significant deterioration in their scattering and absorption resonances at high temperatures. In combination with low dissipative damping, this makes the semiconductor nanoparticles better suited for high-temperature applications in nanoplasmonics wherein the noble metals suffer from excessive heating.
Description: This paper is in closed access.
Sponsor: The authors gratefully acknowledge funding and support from the Academy of Finland, COMP Center of Excellence Programs (2015-2017), Grant No. 284621; QTF Center of Excellence Program, Grant No. 312298; RADDESS Consortium Grant; the Aalto Energy Efficiency Research Program EXPECTS; the Aalto Science-IT project; the Discovery Grants and Canada Research Chairs Program of the Natural Sciences and Engineering Research Council (NSERC) of Canada; and Compute Canada (www.computecanada.ca).
Version: Published
DOI: 10.1002/adts.201800100
URI: https://dspace.lboro.ac.uk/2134/35766
Publisher Link: https://doi.org/10.1002/adts.201800100
ISSN: 2513-0390
Appears in Collections:Closed Access (Maths)

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