Ab Initio Characterization of the CO-Water Interface Using Unsupervised Machine Learning for Dimensionality Reduction.

Precise characterization of the supercritical CO-water interface under high pressure and temperature conditions is crucial for the geological storage of carbon dioxide (CO) in deep saline aquifers. Molecular dynamics (MD) simulations offer a valuable approach to gaining insight into the CO-water interface at a microscopic level. However, no attempt has been made to characterize the CO-water interface with the accuracy afforded by calculations.

Atomic-Scale Insights into the Phase Behavior of Carbon Dioxide and Water from 313 to 573 K and 8 to 30 MPa.

We performed molecular dynamics (MD) simulations of CO + HO systems by employing widely used force fields (EPM2, TraPPE, and PPL models for CO; SPC/E and TIP4P/2005 models for HO). The phase behavior observed in our MD simulations is consistent with the coexistence lines obtained from previous experiments and SAFT-based theoretical models for the equations of state. Our structural analysis reveals a pronounced correlation between phase transitions and the structural orderliness.