Structure and Dynamics of CO2 at the Air–Water Interface from Classical and Neural Network Potentials DOI
Nitesh Kumar, Vyacheslav S. Bryantsev

The Journal of Physical Chemistry Letters, Journal Year: 2025, Volume and Issue: unknown, P. 5619 - 5626

Published: May 29, 2025

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

Language: Английский

On the mutual solubility of water with H2/N2/CO2 gas mixtures under high pressure/temperature conditions relevant to hydrothermal vent chemistry: A co-localized infrared/Raman spectroscopic investigation DOI

G. Bøe,

Thierry Tassaing

Journal of Molecular Liquids, Journal Year: 2025, Volume and Issue: unknown, P. 127204 - 127204

Published: Feb. 1, 2025

Language: Английский

Citations

0
Structure and Dynamics of CO2 at the Air–Water Interface from Classical and Neural Network Potentials DOI
Nitesh Kumar, Vyacheslav S. Bryantsev

The Journal of Physical Chemistry Letters, Journal Year: 2025, Volume and Issue: unknown, P. 5619 - 5626

Published: May 29, 2025

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

Language: Английский

Citations

0