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Convergence of Computed Aqueous Absorption Spectra with Explicit Quantum Mechanical Solvent

Overview of attention for article published in Journal of Chemical Theory and Computation, April 2017
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Article details
Title
Convergence of Computed Aqueous Absorption Spectra with Explicit Quantum Mechanical Solvent
Published in
Journal of Chemical Theory and Computation, April 2017
DOI 10.1021/acs.jctc.7b00159
Pubmed ID
Authors
Abstract

For reliable condensed phase simulations, an accurate model that includes both short- and long-range interactions is required. Short- and long-range interactions may be particularly strong in aqueous solution, where hydrogen-bonding may play a large role at short range and polarization may play a large role at long-range. Although short-range solute-solvent interactions such as charge-transfer, hydrogen bonding, and solute-solvent polarization can be taken into account with a quantum mechanical (QM) treatment of the solvent, it is unclear how much QM solvent is necessary to accurately model interactions with different solutes. In this work, we investigate the effect of explicit QM solvent on absorption spectra computed for a series of solutes with decreasing polarity. By adjusting the boundary between QM and classical molecular mechanical solvent to include up to 400 QM water molecules, convergence of the calculated absorption spectra with respect to the size of the QM region is achieved. We find that the rate of convergence does not correlate with solute polarity when excitation energies are calculated using time dependent density functional theory with a range-separated hybrid functional, but does correlate with solute polarity when using configuration interaction singles. We also find that larger basis sets converge the computed spectrum with fewer QM solvent molecules. To optimize the computational cost with respect to convergence, we test a mixed basis set with more basis functions for atoms of the chromophore and the solvent molecules that are nearest to it and fewer basis functions for the atoms of the remaining solvent molecules in the QM region. Our results show that using a mixed basis sets is potentially an effective way to significantly lower the computational cost while reproducing the results computed with larger basis sets.

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X Demographics

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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
United Kingdom 1 2%
France 1 2%
Unknown 59 97%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 22 36%
Researcher 12 20%
Professor > Associate Professor 7 11%
Student > Master 6 10%
Other 1 2%
Other 4 7%
Unknown 9 15%
Readers by discipline
Readers by discipline Count As %
Chemistry 39 64%
Physics and Astronomy 5 8%
Chemical Engineering 1 2%
Biochemistry, Genetics and Molecular Biology 1 2%
Business, Management and Accounting 1 2%
Other 2 3%
Unknown 12 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 September 2017.
All research outputs
#10,012,073
of 29,418,433 outputs
Outputs from Journal of Chemical Theory and Computation
#2,990
of 8,209 outputs
Outputs of similar age
#131,942
of 332,982 outputs
Outputs of similar age from Journal of Chemical Theory and Computation
#44
of 127 outputs
Altmetric has tracked 29,418,433 research outputs across all sources so far. This one has received more attention than most of these and is in the 65th percentile.
So far Altmetric has tracked 8,209 research outputs from this source. They receive a mean Attention Score of 4.1. This one has gotten more attention than average, scoring higher than 63% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 332,982 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.
We're also able to compare this research output to 127 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.