Assessing Nonbonded Aggregates Populations: Application to the Concentration-Dependent IR O–H Band of Phenol
In this work, we present two alternative computational strategies to determine the populations of nonbonded aggregates. One approach extracts these populations from molecular dynamics (MD) simulations, while the other employs quantum mechanical partition functions for the most relevant minima of the multimolecular potential energy surfaces (PESs), identified by automated conformational sampling. In both cases, we adopt a common graph-theory-based framework, introduced in this work, for identifying aggregate conformations, which enables a consistent comparative assessment of both methodologies and provides insight into the underlying approximations. We apply both strategies to investigate phenol aggregates, up to the tetramer, at different concentrations in phenol/carbon tetrachloride mixtures. Subsequently, we simulate the concentration-dependent OH stretching IR region by averaging the harmonic Infrared (IR) spectra of aggregates using the populations predicted by each strategy. Our results indicate that the populations extracted from MD trajectories yield OH stretching signals that closely follow the experimental trends, outperforming the spectra from populations obtained by systematic conformational searches. Such a better performance of MD is attributed to a better description of the entropic contributions. Moreover, the proposed protocol not only successfully addresses a very challenging problem but also offers a benchmark to assess the accuracy of the intermolecular force fields.
We compare non-bonded aggregate populations from MD vs conformational sampling+partition function. MD wins, better capturing the entropy of conformational flexibility. Bonus: nearly quantitative simulation of the broad OH IR band! Great work by J. Pablo Gálvez!
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pubs.acs.org/doi/full/10....
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