A random forest trained on molecular simulations predicts nanoconfined fluid density profiles across temperatures and pore widths with good interpolation and modest extrapolation.
, author Zhou, R
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How Machine Learning Predicts Fluid Densities under Nanoconfinement
A random forest trained on molecular simulations predicts nanoconfined fluid density profiles across temperatures and pore widths with good interpolation and modest extrapolation.