Solvent Dynamics Are Critical to Understanding Carbon Dioxide Dissolution and Hydration in Water

• Published in: Journal of the American Chemical Society Vol. 145; no. 23; pp. 12561 - 12575
• Main Authors: Martirez, John Mark P., Carter, Emily A.
• Format: Journal Article
• Language: English
• Published: United States American Chemical Society 14.06.2023; American Chemical Society (ACS)
• Subjects: chemical reactions; chemical structure; free energy; INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; molecules; solvation
• ISSN: 0002-7863; 1520-5126
• DOI: 10.1021/jacs.3c01283

Simulations of carbon dioxide (CO2) in water may aid in understanding the impact of its accumulation in aquatic environments and help advance technologies for carbon capture and utilization (via, e.g., mineralization). Quantum mechanical (QM) simulations based on static molecular models with polarizable continuum solvation poorly reproduce the energetics of CO2 hydration to form carbonic acid in water, independent of the level of QM theory employed. Only with density-functional-theory-based molecular dynamics and rare-event sampling, followed by energy corrections based on embedded correlated wavefunction theory (in conjunction with density functional embedding theory), can a close agreement between theory and experiment be achieved. Such multilevel simulations can serve as benchmarks for simpler, less costly models, giving insight into potential errors of the latter. The strong influence of sampling/averaging over dynamical solvent configurations on the energetics stems from the difference in polarity of both the transition state and product (both polar) versus the reactant (nonpolar). When a solute undergoes a change in polarity during reaction, affecting its interaction with the solvent, careful assessment of the energetic contribution of the solvent response to this change is critical. We show that static models (without structural sampling) that incorporate three explicit water molecules can yield far superior results than models with more explicit water molecules because fewer water molecules yield less configurational artifacts. Static models intelligently incorporating both explicit (molecules directly participating in the reaction) and implicit solvation, along with a proper QM theory, e.g., CCSD­(T) for closed-shell systems, can close the accuracy gap between static and dynamic models.