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Evaporation studies of water using classical molecular dynamics simulationsare largely limited due to their high computational expense. This studyaddresses that issue by developing coarse-grained molecular dynamics modelsbased on Morse potential. Models are optimized based on multi-temperature andat room temperature using machine learning techniques like genetic algorithm,Nelder-Mead algorithm, and Strength Pareto Evolutionary Algorithm. Themulti-temperature based model named as Morse-D is found to be more accuratethan single temperature model in representing the water properties at highertemperatures. Using this Morse-D water model, evaporation from hydrophilicnanopores with pore diameter varying from 2 nm to 5 nm is studied. Our resultsshow that the critical diameter to initiate continuous evaporation at nanoporeslies between 3 nm and 4 nm. A maximum heat flux of 21.3 kW/cm2 is observed fora pore diameter of 4.5 nm and a maximum mass flow rate of 16.2 ng/s for a porediameter of 5 nm. The observed heat flux is an order of magnitude times largerthan the currently reported values from experiments in the literature forwater, which indicates that we need to focus on nanoscale evaporation toenhance the critical heat flux.

Critical Diameter for Continuous Evaporation is between 3 nm and 4 nm for Hydrophilic Nanopores