Density functional theory (DFT) study of water autoionization in solvated clusters

We have implemented a cluster-continuum method using density functional theory to model water clusters and various charged species derived from water. The two aims of this study are to determine the minimal basis required for proper modeling of water autoionization and to determine the minimum number of explicit water molecules required to properly model the energetics of solvation. The thermodynamics of water autoionization converge following a modified power law to deliver chemically accurate values of the Gibbs energy change for autoionization with tractably small clusters. Convergence is slower and not exponential as assumed in previous work. We identify the n = 21 set of clusters as the first effectively bulk water like clusters that can capture the energetic influence of both the first and second solvation shells. In this cluster, a water molecule is encapsulated in the center of a closed shell of other water molecules that hydrogen bond to form five-membered rings. The total energy change for clusters with n ≥ 21 calculated using both the RPBE-D3 and ωB97X-D exchange-correlation functionals with the 6-311+G** basis set is shown to deliver good approximations to the free energy change at 298 K. This is true even though neither functional models the individual enthalpy or entropy contributions particularly well.

Authors

Institutions

Publication Details

Journal
The Journal of Chemical Physics
Published
2024-09-16
DOI
https://doi.org/10.1063/5.0221225
Citations
3
Primary Topic
Spectroscopy and Quantum Chemical Studies
Type
article
Field-Weighted Citation Impact
1.01

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Density functional theory (DFT) study of water autoionization in solvated clusters

Kurt W. Kołasiński, Alexa M. Salkowski
3 citations
The Journal of Chemical Physics
Spectroscopy and Quantum Chemical Studies
1.01
article

Density functional theory (DFT) study of water autoionization in solvated clusters

Kurt W. Kołasiński, Alexa M. Salkowski
article en
3 citations

Abstract

We have implemented a cluster-continuum method using density functional theory to model water clusters and various charged species derived from water. The two aims of this study are to determine the minimal basis required for proper modeling of water autoionization and to determine the minimum number of explicit water molecules required to properly model the energetics of solvation. The thermodynamics of water autoionization converge following a modified power law to deliver chemically accurate values of the Gibbs energy change for autoionization with tractably small clusters. Convergence is slower and not exponential as assumed in previous work. We identify the n = 21 set of clusters as the first effectively bulk water like clusters that can capture the energetic influence of both the first and second solvation shells. In this cluster, a water molecule is encapsulated in the center of a closed shell of other water molecules that hydrogen bond to form five-membered rings. The total energy change for clusters with n ≥ 21 calculated using both the RPBE-D3 and ωB97X-D exchange-correlation functionals with the 6-311+G** basis set is shown to deliver good approximations to the free energy change at 298 K. This is true even though neither functional models the individual enthalpy or entropy contributions particularly well.

The Journal of Chemical PhysicsVol. 161(11)
West Chester University (US)
West Chester University
Clean water and sanitation
Openalex Percentile: Top 25%
Spectroscopy and Quantum Chemical Studies
1.01
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.