Hydrogen-Bond Topology Is More Important Than Acid/Base Strength in Atmospheric Prenucleation Clusters

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 major 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 clusters (AMC), denoted AMC-xTB. The AMC-xTB model reduces the mean of electronic binding energy errors from 7-11.8 kcal mol-1 to roughly 0 kcal mol-1 and the root mean square deviation from 7.6-12.3 kcal mol-1 to 0.81-1.45 kcal mol-1. 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", is 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-1. Lastly, by employing the improvement workflow we massively screened 288 new multi-acid-multi-base clusters containing up to 8 different species. For these new multi-acid-multi-base 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-1, but we see improvements up to 8.3 kcal mol-1. Hence, we can recommend this new workflow based on the AMC-xTB model for future studies on atmospheric molecular clusters.

Structural Diversity of Protonated Citric Acid-Ammonia Clusters and Its Atmospheric Implication

Various acid-base molecular clusters involving organic species can serve as precursors that play important roles in the formation of an atmospheric aerosol. Due to its structural flexibility and its ability to form multiple hydrogen bonds, citric acid acts as a key species in forming clusters that are critical in the nucleation of related aerosol precursors. Thus, it is provoking to characterize the structures of these clusters at the molecular level. In this paper, protonated citric acid-ammonia clusters of various sizes were generated by electrospray ionization and studied by tandem mass spectrometry. The structures of [(CA)2+NH4]1+ and [(CA)4+NH4]1+ were further characterized by the method of infrared photodissociation (IRPD) spectroscopy. Combined with theoretical calculations, it is found that the most stable structures of the dimeric and tetrameric isomers show the shapes of an ingot and a lantern, respectively. It has been revealed that the temperature has a great effect on the contributions of different isomers for both dimers and tetramers. The dominat isomers are found to have more open structures at higher temperatures, facilitating the growth of clusters through new hydrogen bonds.

Current and future machine learning approaches for modeling atmospheric cluster formation

The formation of strongly bound atmospheric molecular clusters is the first step towards forming new aerosol particles. Recent advances in the application of machine learning models open an enormous opportunity for complementing expensive quantum chemical calculations with efficient machine learning predictions. In this Perspective, we present how data-driven approaches can be applied to accelerate cluster configurational sampling, thereby greatly increasing the number of chemically relevant systems that can be covered.

Clusteromics V: Organic Enhanced Atmospheric Cluster Formation

Formic acid (FA) is a prominent candidate for organic enhanced nucleation due to its high abundance and stabilizing effect on smaller clusters. Its role in new particle formation is studied through the use of state-of-the-art quantum chemical methods on the cluster systems (acid)_1-2(FA)₁(base)_1-2 with the acids being sulfuric acid (SA)/methanesulfonic acid (MSA) and the bases consisting of ammonia (A), methylamine (MA), dimethylamine (DMA), trimethylamine (TMA), and ethylenediamine (EDA). A funneling approach is used to determine the cluster structures with initial configurations generated through the ABCluster program, followed by semiempirical PM7 and ωB97X-D/6-31++G(d,p) calculations. The final binding free energy is calculated at the DLPNO-CCSD(T₀)/aug-cc-pVTZ//ωB97X-D/6-31++G(d,p) level of theory using the quasi-harmonic approximation. Cluster dynamics simulations show that FA has a minuscule or negligible effect on the MSA-FA-base systems as well as most of the SA-FA-base systems. The SA-FA-DMA cluster system shows the highest influence from FA with an enhancement of 21%, compared to its non-FA counterpart.

The role of hydration in atmospheric salt particle formation

New-particle formation from condensable acid and base molecules is a ubiquitous phenomenon in the atmosphere. The role of water in salt particle formation is not fully understood as it can stabilize or destabilize cluster structures, which leads to non-linear effects on cluster formation dynamics. In the studied systems, increased relative humidity can enhance the particle formation for up to four orders of magnitude in the case of nitric acid, but it can also slightly reduce the particle formation in the cases of sulfuric acid and methanesulfonic acid. As the effect of relative humidity in salt particle formation varies many orders of magnitude depending on the acid and base molecules, neglecting hydration or using the same value for different systems may introduce remarkable inaccuracies in large-scale models.

Massive Assessment of the Binding Energies of Atmospheric Molecular Clusters

Quantum chemical studies of the formation and growth of atmospheric molecular clusters are important for understanding aerosol particle formation. However, the search for the lowest free-energy cluster configuration is extremely time consuming. This makes high-level benchmark data sets extremely valuable in the quest for the global minimum as it allows the identification of cost-efficient computational methodologies, as well as the development of high-level machine learning (ML) models. Herein, we present a highly versatile quantum chemical data set comprising a total of 11 749 (acid)_1-2(base)_1-2 cluster configurations, containing up to 44 atoms. Utilizing the LUMI supercomputer, we calculated highly accurate PNO-CCSD(F12*)(T)/cc-pVDZ-F12 binding energies of the full set of cluster configurations leading to an unprecedented data set both in regard to sheer size and with respect to the level of theory. We employ the constructed benchmark set to assess the performance of various semiempirical and density functional theory methods. In particular, we find that the r²-SCAN-3c method shows excellent performance across the data set related to both accuracy and CPU time, making it a promising method to employ during cluster configurational sampling. Furthermore, applying the data sets, we construct ML models based on Δ-learning and provide recommendations for future application of ML in cluster configurational sampling.

The driving effects of common atmospheric molecules for formation of prenucleation clusters: the case of sulfuric acid, formic acid, nitric acid, ammonia, and dimethyl amine

How secondary aerosols form is critical as aerosols' impact on Earth's climate is one of the main sources of uncertainty for understanding global warming. The beginning stages for formation of prenucleation complexes, that lead to larger aerosols, are difficult to decipher experimentally. We present a computational chemistry study of the interactions between three different acid molecules and two different bases. By combining a comprehensive search routine covering many thousands of configurations at the semiempirical level with high level quantum chemical calculations of approximately 1000 clusters for every possible combination of clusters containing a sulfuric acid molecule, a formic acid molecule, a nitric acid molecule, an ammonia molecule, a dimethylamine molecule, and 0-5 water molecules, we have completed an exhaustive search of the DLPNO-CCSD(T)/CBS//ωB97X-D/6-31++G** Gibbs free energy surface for this system. We find that the detailed geometries of each minimum free energy cluster are often more important than traditional acid or base strength. Addition of a water molecule to a dry cluster can enhance stabilization, and we find that the (SA)(NA)(A)(DMA)(W) cluster has special stability. Equilibrium calculations of SA, FA, NA, A, DMA, and water using our quantum chemical ΔG° values for cluster formation and realistic estimates of the concentrations of these monomers in the atmosphere reveals that nitric acid can drive early stages of particle formation just as efficiently as sulfuric acid. Our results lead us to believe that particle formation in the atmosphere results from the combination of many different molecules that are able to form highly stable complexes with acid molecules such as SA, NA, and FA.

Interaction of Glutamic Acid/Protonated Glutamic Acid with Amide and Water Molecules: A Theoretical Study

Amino acids are important nitrogen-containing compounds and organic carbon components that exist widely in the atmosphere. The formation of atmospheric aerosols is affected by their interactions with amides. The dimers formed by glutamic acid (Glu) or protonated glutamic acid (Glu⁺) with three kinds of amide molecules (formamide FA, acetamide AA, urea U) and the hydrated clusters formed by Glu or Glu⁺, U molecules along with one to six water molecules were systematically studied at the M06-2X/6-311++G(3df,3pd) level. U is predicted to form a more stable structure with Glu/Glu⁺ than FA and AA by thermodynamics. If the concentration ratio of FA to U is less than 10⁴, U will play a critical role in NPF. The degree of hydration in Glu⁺-mU-nW is higher than that of Glu-mU-nW (m = 0, 1; n = 0-6) clusters. Notably, Glu contributes more to the Rayleigh scattering properties than glutaric acid and sulfuric acid, and thus may lead to the destruction of atmospheric visibility. This study is helpful to better understand the properties of organic aerosols containing amino acids or amides.

Clusteromics IV: The Role of Nitric Acid in Atmospheric Cluster Formation

Nitric acid (NA) has previously been shown to affect atmospheric new particle formation; however, its role still remains highly uncertain. Through the employment of state-of-the-art quantum chemical methods, we study the (acid)_1-2(base)_1-2 and (acid)₃(base)₂ clusters containing at least one nitric acid (NA) and sulfuric acid (SA) or methanesulfonic acid (MSA) with bases ammonia (A), methylamine (MA), dimethylamine (DMA), trimethylamine (TMA), and ethylenediamine (EDA). The initial cluster configurations are generated using the ABCluster program. PM7 and ωB97X-D/6-31++G(d,p) calculations are used to reduce the number of relevant configurations. The thermochemical parameters are calculated at the ωB97X-D/6-31++G(d,p) level of theory with the quasi-harmonic approximation, and the final single-point energies are calculated with high-level DLPNO-CCSD(T₀)/aug-cc-pVTZ calculations. The enhancing effect from the presence of nitric acid on cluster formation is studied using the calculated thermochemical data and cluster dynamics simulations. We find that when NA is in excess compared with the other acids, it has a substantial enhancing effect on the cluster formation potential.

Amino Acids Compete with Ammonia in Sulfuric Acid-Based Atmospheric Aerosol Prenucleation: The Case of Glycine and Serine

We present a computational investigation of the sulfuric acid, glycine, serine, ammonia, and water system to understand if this system can form prenucleation clusters, which are precursors to larger aerosols in the atmosphere. We have performed a comprehensive configurational search of all possible clusters in this system, starting with the four different monomers and zero to five waters. Accurate Gibbs free energies of formation have been calculated with the DLPNO-CCSD(T)/complete basis set (CBS) method on ωb97xd/6-31++G** geometries. For the dry dimers of sulfuric acid, the weakest base, serine, is found to form the most stable complex, which is a consequence of the strong di-ionic complex formed between the bisulfate ion and the protonated serine cation. For the dry dimers without sulfuric acid, the glycine-serine complex is more stable than the glycine-ammonia or serine-ammonia complexes, stemming from the detailed structure and not related to base strength. For the larger complexes, sulfuric acid deprotonates and the proton is shifted to glycine, serine, or ammonia. The two amino acids and ammonia are almost interchangeable and there is no easy way to predict which molecule will be protonated without the calculated results. Assuming reasonable starting concentrations and a closed system of sulfuric acid, glycine, serine, ammonia, and five waters, we predict the concentrations of all possible complexes at two temperatures spanning the troposphere. The most negative ΔG° values are a function of the detailed molecular interactions of these clusters. These details are more important than the base strength of ammonia, glycine, and serine.

Clusteromics III: Acid Synergy in Sulfuric Acid-Methanesulfonic Acid-Base Cluster Formation

Acid-base molecular clusters are an important stage in atmospheric new particle formation. While such clusters are most likely multicomponent in nature, there are very few reports on clusters consisting of multiple acid molecules and multiple base molecules. By applying state-of-the-art quantum chemical methods, we herein study electrically neutral (SA)₁(MSA)₁(base)_0-2 clusters with base = ammonia (A), methylamine (MA), dimethylamine (DMA), trimethylamine (TMA) and ethylenediamine (EDA). The cluster structures are obtained using a funneling approach employing the ABCluster program, semiempirical PM7 calculations and ωB97X-D/6-31++G(d,p) calculations. The final binding free energies are calculated at the DLPNO-CCSD(T₀)/aug-cc-pVTZ//ωB97X-D/6-31++G(d,p) level of theory using the quasi-harmonic approximation. Based on the calculated cluster geometries and thermochemistry (at 298.15 K and 1 atm), we find that the mixed (SA)₁(MSA)₁(base)_1-2 clusters more resemble the (SA)₂(base)_1-2 clusters compared to the (MSA)₂(base)_1-2 clusters. Hence, some of the steric hindrance and lack of hydrogen bond capacity previously observed in the (MSA)₂(base)_1-2 clusters is diminished in the corresponding (SA)₁(MSA)₁(base)_1-2 clusters. Cluster kinetics simulations reveal that the presence of an MSA molecule in the clusters enhances the cluster formation potential by up to a factor of 20. We find that the SA-MSA-DMA clusters have the highest cluster formation potential, and thus, this system should be further extended to larger sizes in future studies.