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.

While the intrinsically multi-scale nature of most advanced materials necessitates the use of cost-effective computational models based on classical physics, a reliable description of the structure an...