Author:
Wang Xiaoman,Ghaffarizadeh S. Arman,He Xiao,McGaughey Alan J. H.,Malen Jonathan A.
Abstract
AbstractThin film evaporation is a widely-used thermal management solution for micro/nano-devices with high energy densities. Local measurements of the evaporation rate at a liquid-vapor interface, however, are limited. We present a continuous profile of the evaporation heat transfer coefficient ($$h_{\text {evap}}$$
h
evap
) in the submicron thin film region of a water meniscus obtained through local measurements interpreted by a machine learned surrogate of the physical system. Frequency domain thermoreflectance (FDTR), a non-contact laser-based method with micrometer lateral resolution, is used to induce and measure the meniscus evaporation. A neural network is then trained using finite element simulations to extract the $$h_{\text {evap}}$$
h
evap
profile from the FDTR data. For a substrate superheat of 20 K, the maximum $$h_{\text {evap}}$$
h
evap
is $$1.0_{-0.3}^{+0.5}$$
1
.
0
-
0.3
+
0.5
MW/$$\text {m}^2$$
m
2
-K at a film thickness of $$15_{-3}^{+29}$$
15
-
3
+
29
nm. This ultrahigh $$h_{\text {evap}}$$
h
evap
value is two orders of magnitude larger than the heat transfer coefficient for single-phase forced convection or evaporation from a bulk liquid. Under the assumption of constant wall temperature, our profiles of $$h_{\text {evap}}$$
h
evap
and meniscus thickness suggest that 62% of the heat transfer comes from the region lying 0.1–1 μm from the meniscus edge, whereas just 29% comes from the next 100 μm.
Funder
Division of Chemical, Bioengineering, Environmental, and Transport Systems
Natural Sciences and Engineering Research Council of Canada
Publisher
Springer Science and Business Media LLC
Cited by
1 articles.
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