Structure and Dynamics of CO2 at the Air-Water Interface from Classical and Neural Network Potentials

The accurate description of the structure and dynamics of CO2 at the instantaneous air-water interface, along with the effects of surface fluctuations on the CO2-transport processes, is essential for the development of negative emission technologies aimed to mitigate climate change. In this study, we performed molecular dynamics simulations of CO2 at the air-water interface using neural network potentials (NNPs) trained on ab initio data generated through density functional theory-based molecular dynamics simulations. We compared these results with classical force fields to assess their performance in modeling interfacial CO2 behavior. Our findings revealed that the asymmetric interactions, coupled with thermal surface fluctuations at the air-water interface signif- icantly influence CO2 transport into the aqueous phase. The simulations demonstrate that classical force fields underestimate both the free energy of CO2 transport and the strength of its interactions at the interface compared to the neural network potentials. The free energy and the interfacial dynamics of CO2 are primarily influenced by the distribution of water within the instantaneous interfacial water layer, responsible for creating asymmetric intermolecular interaction environment within the interfacial region.