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Open Access Publications from the University of California

Engineering Nanoscale Thermal Transport: Size- and Spacing-Dependent Cooling of Nanostructures

  • Author(s): Frazer, TD
  • Knobloch, JL
  • Hoogeboom-Pot, KM
  • Nardi, D
  • Chao, W
  • Falcone, RW
  • Murnane, MM
  • Kapteyn, HC
  • Hernandez-Charpak, JN
  • et al.

Nanoscale thermal transport is becoming ever more technologically important with the development of next-generation nanoelectronics, nanomediated thermal therapies, and high efficiency thermoelectric devices. However, direct experimental measurements of nondiffusive heat flow in nanoscale systems are challenging, and first-principle models of real geometries are not yet computationally feasible. In recent work, we used ultrafast pulses of short-wavelength light to uncover a previously-unobserved regime of nanoscale thermal transport that occurs when the width and separation of heat sources are comparable to the mean free paths of the dominant heat-carrying phonons in the substrate. We now systematically compare thermal transport from gratings of metallic nanolines with different periodicities, on both silicon and fused-silica substrates, to map the entire nanoscale thermal transport landscape - from closely spaced through increasingly isolated to fully isolated heat-transfer regimes. By monitoring the surface profile dynamics with subangstrom sensitivity, we directly measure thermal transport from the nanolines into the substrate. This allows us to quantify for the first time how the nanoline separation significantly impacts thermal transport into the substrate, making it possible to reach efficiencies that are within a factor of 2 of the diffusive (i.e., thin-film) limit. We also show that partially isolated nanolines perform significantly worse, because cooling occurs in a regime that is intermediate between close-packed and fully isolated heat sources. This work thus confirms the surprising prediction that closely spaced nanoscale heat sources can cool more quickly than when far apart. These results show that our predictive model is validated by experiment over a broad parameter space, which is important for benchmarking theories that go beyond the Fourier model of heat diffusion, and for informed design of nanoengineered systems.

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