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 at minimizing 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, significantly 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 with 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 an asymmetric intermolecular interaction environment within the interfacial region.