Acidity constants from vertical energy gaps: density functional theory based molecular dynamics implementation

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发布日期 2008-07-03
DOI 10.1039/B802376J
影响因子 3.676
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摘要

The question of how to compute acidity constants (pKa) treating solvent and solute at the same level of theory remains of some interest, for example in the case of high or low pH conditions. We have developed a density functional theory based molecular dynamics implementation of such a method. The method is based on a half reaction scheme computing free energies of dissociation from the vertical energy gaps for insertion or removal of protons. Finite system size effects are important, but largely cancel when half reactions are combined to full reactions. We verified the method by investigating a series of organic and inorganic acids and bases spanning a wide range of pKa values (20 units). We find that the response of the aqueous solvent to vertical protonation/deprotonation is almost always asymmetric and correlated with the strength of the hydrogen bonding of the deprotonated base. We interpret these observations in analogy with the picture of solvent response to electronic ionization.

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来源期刊

Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
自引率: 10.3%
年发文量: 3036

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.

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