Machine-Learned Free Energy Surfaces for Capillary Condensation and Evaporation in Mesopores

Using molecular simulations, we study the processes of capillary condensation and capillary evaporation in model mesopores. To determine the phase transition pathway, as well as the corresponding free energy profile, we carry out enhanced sampling molecular simulations using entropy as a reaction coordinate to map the onset of order during the condensation process and of disorder during the evaporation process. The structural analysis shows the role played by intermediate states, characterized by the onset of capillary liquid bridges and bubbles. We also analyze the dependence of the free energy barrier on the pore width. Furthermore, we propose a method to build a machine learning model for the prediction of the free energy surfaces underlying capillary phase transition processes in mesopores.

Automated summary

In this study, molecular simulations are used to investigate capillary condensation and evaporation processes in model mesopores. The results reveal the role of intermediate states characterized by the formation of capillary liquid bridges and bubbles. Additionally, a machine learning model is proposed for predicting the free energy surfaces underlying capillary phase transition processes in mesopores.