The frequency domain perfectly matched layer (FDPML) approach is used to study phonon transport in a series of large 2D domains with randomly embedded nanoparticles over a wide range of nanoparticle loadings and wavelengths. The effect of nanoparticle packing density on the mean free path and localization length is characterized. We observe that, in the Mie scattering regime, the independent scattering approximation is valid up to volume fractions exceeding 10% and often higher depending on scattering parameter, indicating that the mean free path can usually be calculated much less expensively using the number density and the scattering cross section of a single scatterer. We also study localization lengths and their dependence on particle loading. For heavy nanoparticles embedded in a lighter material, using the FDPML approach, we only observe localization at volume fractions [Formula: see text] and only for short wavelength modes where vibrational frequencies exceed those available in the embedded nanoparticles. Using modal analysis, we show that localization in nanoparticle laden materials is primarily due to energetic confinement rather than Anderson localization. We then show that, by using light particles in a heavy matrix, the fraction of confined modes can be substantially increased.
This content will become publicly available on November 15, 2024
Nanoparticles embedded within a crystalline solid serve as impurity phonon scattering centers that reduce lattice thermal conductivity, a desirable result for thermoelectric applications. Most studies of thermal transport in nanoparticle-laden composite materials have assumed the nanoparticles to possess a single size. If there is a distribution of nanoparticle sizes, how is thermal conductivity affected? Moreover, is there a best nanoparticle size distribution to minimize thermal conductivity? In this work, we study the thermal conductivity of nanoparticle-laden composites through a molecular dynamics approach which naturally captures phonon scattering processes more rigorously than previously used analytical theories. From thermal transport simulations of a systematic variety of nanoparticle configurations, we empirically formulate how nanoparticle size distribution, particle number density, and volume fraction affect the lattice thermal conductivity. We find at volume fractions below 10%, the particle number density is by far the most impactful factor on thermal conductivity and at fractions above 10%, the effect of the size distribution and number density is minimal compared to the volume fraction. In fact, upon comparisons of configurations with the same particle number density and volume fractions, the lattice thermal conductivity of a single nanoparticle size can be lower than that of a size distribution which contradicts intuitions that a single size would attenuate phonon transport less than a spectrum of sizes. The random alloy, which can be considered as a single size configuration of maximum particle number density where the nanoparticle size is equal to the lattice constant, is the most performant in thermal conductivity reduction at volume fractions below 10%. We conclude that nanoparticle size distribution only plays a minor role in affecting lattice thermal conductivity with the particle number density and volume fraction being the more significant factors that should be considered in fabrication of nanoparticle-laden composites for potential improved thermoelectric performance.
more » « less- Award ID(s):
- 2047109
- NSF-PAR ID:
- 10474053
- Publisher / Repository:
- IOP Publishing
- Date Published:
- Journal Name:
- Nanotechnology
- Volume:
- 35
- Issue:
- 5
- ISSN:
- 0957-4484
- Page Range / eLocation ID:
- 055701
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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