Thermal transport from 1D- and 2D-confined nanostructures on silicon probed using coherent extreme UV light: General and predictive model yields new understanding

Abstract

Heat management is crucial in the design of nanoscale devices as the operating temperature determines their efficiency and lifetime. Past experimental and theoretical works exploring nanoscale heat transport in semiconductors addressed known deviations from Fourier's law modeling by including effective parameters, such as a size-dependent thermal conductivity. However, recent experiments have qualitatively shown new behavior that cannot be modeled in this way. Here, we combine advanced experiment and theory to show that the cooling of 1D- and 2D-confined nanoscale hot spots on silicon can be described using a general hydrodynamic heat transport model, contrary to previous understanding of heat flow in bulk silicon. We use a comprehensive set of extreme ultraviolet scatterometry measurements of non-diffusive transport from transiently heated nanolines and nanodots to validate and generalize our ab initio model, that does not need any geometry-dependent fitting parameters. This allows us to uncover the existence of two distinct timescales and heat transport mechanisms: an interface resistance regime that dominates on short time scales, and a hydrodynamic-like phonon transport regime that dominates on longer timescales. Moreover, our model can predict the full thermomechanical response on nanometer length scales and picosecond time scales for arbitrary geometries, providing an advanced practical tool for thermal management of nanoscale technologies. Furthermore, we derive analytical expressions for the transport timescales, valid for a subset of geometries, supplying a route for optimizing heat dissipation.

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Cited by in corpus (4)

• Universal behavior of highly-confined heat flow in semiconductor nanosystems: from nanomeshes to metalattices
• Theory of Transient Heat Conduction
• Non-monotonic heat dissipation phenomenon in close-packed quasi-2D and 3D hotspot system
• Descriptors of intrinsic hydrodynamic thermal transport: screening a phonon database in a machine learning approach