Measurement and Multilayer Model of Cooling of Gold Nanoparticles: Transient Thermoreflectance Experiments and Multilayer Analytical Modeling
Publication Date
10-14-2018
Document Type
Article
Organizational Units
College of Natual Science and Mathematics, Physics and Astronomy
Keywords
Thermal conductivity, Thermodynamic states and processes, Thermodynamic properties, Ultrafast pump probe spectroscopy, Phonons, Thermal transport, Signal processing, Nanoscale thermodynamics, Nanoparticles, Polymers
Abstract
We derive an analytical model of diffusive thermal transport in multilayer structures of spherical symmetry and apply it to transient thermoreflectance measurements of gold nanoparticles embedded in a polymer matrix. This multilayer approach significantly improves the quantitative measurement of material thermal properties, in comparison with single-layer methods. The model adapts the typical planar transfer matrix model to a spherical geometry, and we apply it to transient thermoreflectance (TTR) experiments on gold nanoparticles embedded in a polymer matrix, to published TTR data for aqueous platinum nanoparticles, and also to example systems of aqueous gold and platinum nanoparticles. We measure a thermal boundary conductance value of 410MW/m2K" role="presentation" style="display: inline; line-height: normal; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; margin: 0px; position: relative;">410MW/m2K410MW/m2K at the nanoparticle gold/polymer interface. The sensitivity of the TTR signal to system thermal properties is predicted as a function of the particle/matrix thermal boundary resistance (TBR), and we discuss the differentiation of TBR and capping layer effects on a TTR signal.
Publication Statement
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Recommended Citation
Green, Brian G, et al. “Measurement and Multilayer Model of Cooling of Gold Nanoparticles: Transient Thermoreflectance Experiments and Multilayer Analytical Modeling.” Journal of Applied Physics, vol. 124, no. 14, 2018, p. 144301. doi: 10.1063/1.5048813.