Abstract
Thin 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 ([Formula: see text]) 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 [Formula: see text] profile from the FDTR data. For a substrate superheat of 20 K, the maximum [Formula: see text] is [Formula: see text] MW/[Formula: see text]-K at a film thickness of [Formula: see text] nm. This ultrahigh [Formula: see text] 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 [Formula: see text] 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.