Reparameterization of GFN1-xTB for Atmospheric Molecular Clusters: Applications to Multi-Acid–Multi-Base Systems

Atmospheric molecular clusters, the onset of secondary aerosol formation, are a ma- jor part of the current uncertainty in modern climate models. Quantum chemical (QC) methods are usually employed in a funneling approach to identify the lowest free energy cluster structures. However, the funneling approach highly depends on the accuracy of low-cost methods to ensure that important low-lying minima are not missed. Here we present a reparameterized GFN1-xTB model based on the Clusteromics I–V datasets for studying atmospheric molecular (AMC) clusters, denoted AMC-xTB. The AMC- xTB model reduces the mean of electronic binding energy errors from 7–11.8 kcal/mol to roughly 0 kcal/mol and the root mean square deviation from 7.6–12.3 kcal/mol to 0.81–1.45 kcal/mol. In addition, the minimum structures obtained with AMC-xTB are closer to the ωB97X-D/6-31++G(d,p) level of theory compared to GFN1-xTB. We employ the new parameterization in two new configurational sampling workflows that include an additional meta-dynamics sampling step using CREST with the AMC-xTB model. The first workflow, denoted the “independent workflow”, is a commonly used funneling approach with an additional CREST step, and the second, the “improvement workflow”, where the best configuration currently known in the literature is improved with a CREST+AMC-xTB step. Testing the new workflow we find configurations lower in free energy for all the literature clusters with the largest improvement being up to 21 kcal/mol. Lastly, employing the improvement workflow we massively screened 288 multi-acid– multi-base clusters containing up to 8 different species. For these new multi-acid–multi- cluster systems we observe that the improvement workflow finds configurations lower in free energy for 245 out of 288 (85.1%) cluster structures. Most of the improvements are within 2 kcal/mol, but we see improvements up to 8.3 kcal/mol. Hence, we can recommend this new workflow based on the AMC-xTB model for future studies on atmospheric molecular clusters.