Hydration of Atmospheric Molecular Clusters: A New Method for Systematic Configurational Sampling

Iodine Clusters in the Atmosphere I: Computational Benchmark and Dimer Formation of Oxyacids and Oxides

The contribution of iodine-containing compounds to atmospheric new particle formation is still not fully understood, but iodic acid and iodous acid are thought to be significant contributors. While several quantum chemical studies have been carried out on clusters containing iodine, there is no comprehensive benchmark study quantifying the accuracy of the applied methods. Here, we present the first study in a series that investigate the role of iodine species in atmospheric cluster formation. In this work, we have studied the iodic acid, iodous acid, iodine tetroxide, and iodine pentoxide monomers and their dimers formed with common atmospheric precursors. We have tested the accuracy of commonly applied methods for calculating the geometry of the monomers, thermal corrections of monomers and dimers, the contribution of spin-orbit coupling to monomers and dimers, and finally, the accuracy of the electronic energy correction calculated at different levels of theory. We find that optimizing the structures either at the ωB97X-D3BJ/aug-cc-pVTZ-PP or the M06-2X/aug-cc-pVTZ-PP level achieves the best thermal contribution to the binding free energy. The electronic energy correction can then be calculated at the ZORA-DLPNO-CCSD(T0) level with the SARC-ZORA-TZVPP basis for iodine and ma-ZORA-def2-TZVPP for non-iodine atoms. We applied this methodology to calculate the binding free energies of iodine-containing dimer clusters, where we confirm the qualitative trends observed in previous studies. However, we identify that previous studies overestimate the stability of the clusters by several kcal/mol due to the neglect of relativistic effects. This means that their contributions to the currently studied nucleation pathways of new particle formation are likely overestimated.

Computational Tools for Handling Molecular Clusters: Configurational Sampling, Storage, Analysis, and Machine Learning

Computational modeling of atmospheric molecular clusters requires a comprehensive understanding of their complex configurational spaces, interaction patterns, stabilities against fragmentation, and even dynamic behaviors. To address these needs, we introduce the Jammy Key framework, a collection of automated scripts that facilitate and streamline molecular cluster modeling workflows. Jammy Key handles file manipulations between varieties of integrated third-party programs. The framework is divided into three main functionalities: (1) Jammy Key for configurational sampling (JKCS) to perform systematic configurational sampling of molecular clusters, (2) Jammy Key for quantum chemistry (JKQC) to analyze commonly used quantum chemistry output files and facilitate database construction, handling, and analysis, and (3) Jammy Key for machine learning (JKML) to manage machine learning methods in optimizing molecular cluster modeling. This automation and machine learning utilization significantly reduces manual labor, greatly speeds up the search for molecular cluster configurations, and thus increases the number of systems that can be studied. Following the example of the Atmospheric Cluster Database (ACDB) of Elm (ACS Omega, 4, 10965-10984, 2019), the molecular clusters modeled in our group using the Jammy Key framework have been stored in an improved online GitHub repository named ACDB 2.0. In this work, we present the Jammy Key package alongside its assorted applications, which underline its versatility. Using several illustrative examples, we discuss how to choose appropriate combinations of methodologies for treating particular cluster types, including reactive, multicomponent, charged, or radical clusters, as well as clusters containing flexible or multiconformer monomers or heavy atoms. Finally, we present a detailed example of using the tools for atmospheric acid-base clusters.

Continuous symmetry and chirality measures: approximate algorithms for large molecular structures

Quantifying imperfect symmetry of molecules can help explore the sources, roles and extent of structural distortion. Based on the established methodology of continuous symmetry and chirality measures, we develop a set of three-dimensional molecular descriptors to estimate distortion of large structures. These three-dimensional geometrical descriptors quantify the gap between the desirable symmetry (or chirality) and the actual one. They are global parameters of the molecular geometry, intuitively defined, and have the ability to detect even minute structural changes of a given molecule across chemistry, including organic, inorganic, and biochemical systems. Application of these methods to large structures is challenging due to countless permutations that are involved in the symmetry operations and have to be accounted for. Our approach focuses on iteratively finding the approximate direction of the symmetry element in the three-dimensional space, and the relevant permutation. Major algorithmic improvements over previous versions are described, showing increased accuracy, reliability and structure preservation. The new algorithms are tested for three sets of molecular structures including pillar[5]arene complexes with Li+, C100 fullerenes, and large unit cells of metal organic frameworks. These developments complement our recent algorithms for calculating continuous symmetry and chirality measures for small molecules as well as protein homomers, and simplify the usage of the full set of measures for various research goals, in molecular modeling, QSAR and cheminformatics.

Toward Modeling the Growth of Large Atmospheric Sulfuric Acid-Ammonia Clusters

Studying large atmospheric molecular clusters is needed to understand the transition between clusters and aerosol particles. In this work, we studied the (SA)n(AM)n clusters with n up to 30 and the (SA)m(AM)m±2 clusters, with m = 6-20. The cluster configurations are sampled using the ABCluster program, and the cluster geometries and thermochemical parameters are calculated using GFN1-xTB. The cluster binding energies are calculated using B97-3c. We find that the addition of sulfuric acid is preferred to the addition of ammonia. The addition free energies were found to have large uncertainties, which could potentially be attributed to errors in the applied level of theory. Based on DLPNO-CCSD(T0)/aug-cc-pVTZ benchmarks of the binding energies of the large (SA)8-9(AM)10 and (SA)10(AM)10-11 clusters, we find that ωB97X-D3BJ with a large basis set is required to yield accurate binding and addition energies. However, based on recalculations of the single-point energy at r2SCAN-3c and ωB97X-D3BJ/6-311++G(3df,3pd), we show that the single-point energy contribution is not the primary source of error. We hypothesize that a larger source of error might be present in the form of insufficient configurational sampling. Finally, we train Δ machine learning model on (SA)n(AM)n clusters with n up to 5 and show that we can predict the binding energies of clusters up to sizes of (SA)30(AM)30 with a binding energy error below 0.6 %. This is an encouraging approach for accurately modeling the binding energies of large acid-base clusters in the future.

Thermodynamic and optical properties of HCOOH(H2O)n and HCOOH(NH3)(H2O)(n-1) clusters at various temperatures and pressures: a computational study

Density functional theory has been used to compute the gas-phase geometries, binding energies, ZPE-corrected binding energies, BSSE-corrected binding energies, binding enthalpies, and binding free energies of HCOOH(H₂O)_n and HCOOH(NH₃)(H₂O)_(n-1) clusters with n = 1-8, 10, 12, 14, 16, 18, and 20. Enthalpies and free energies are calculated for a range of atmospherically relevant temperatures (T) and pressures (P) (from T = 298.15 K, P = 1013.25 hPa to T = 216.65 K, P = 226.32 hPa). The optical properties of those clusters have been studied at the CAM-B3LYP/aug-cc-pVDZ level of theory.

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.

A Statistical Perspective on Microsolvation

The lack of a procedure to determine equilibrium thermodynamic properties of a small system interacting with a bath is frequently seen as a weakness of conventional statistical mechanics. A typical example for such a small system is a solute surrounded by an explicit solvation shell. One way to approach this problem is to enclose the small system of interest in a large bath of explicit solvent molecules, considerably larger than the system itself. The explicit inclusion of the solvent degrees of freedom is obviously limited by the available computational resources. A potential remedy to this problem is a microsolvation approach where only a few explicit solvent molecules are considered and surrounded by an implicit solvent bath. Still, the sampling of the solvent degrees of freedom is challenging with conventional grand canonical Monte Carlo methods, since no single chemical potential for the solvent molecules can be defined in the realm of small-system thermodynamics. In this work, a statistical thermodynamic model based on the grand canonical ensemble is proposed that avoids the conventional system size limitations and accurately characterizes the properties of the system of interest subject to the thermodynamic constraints of the bath. We extend an existing microsolvation approach to a generalized multibath "microstatistical" model and show that the previously derived approaches result as a limit of our model. The framework described here is universal and we validate our method numerically for a Lennard-Jones model fluid.

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.

Contribution of Methanesulfonic Acid to the Formation of Molecular Clusters in the Marine Atmosphere

Because of the lack of long-term measurements, new particle formation (NPF) in the marine atmosphere remains puzzling. Using quantum chemical methods, this study elucidates the cluster formation and further growth of sulfuric acid-methanesulfonic acid-dimethylamine (SA-MSA-DMA) clusters, relevant to NPF in the marine atmosphere. The cluster structures and thermochemical parameters of (SA)_n(MSA)_m(DMA)_l (n + m ≤ 4 and l ≤ 4) systems are calculated using density functional theory at the ωB97X-D/6-31++G(d,p) level of theory, and the single-point energies are calculated using high-level DLPNO-CCSD(T₀)/aug-cc-pVTZ calculations. The calculated thermochemistry is used as input to the Atmospheric Cluster Dynamics Code (ACDC) to gain insight into the cluster dynamics. At ambient conditions (298.15 K, 1 atm), we find that the distribution of outgrowing clusters primarily consists of SA and DMA, with a minor contribution from the mixed SA-MSA-DMA clusters. At lower temperature (278.15 K, 1 atm) the distribution broadens, and clusters containing one or more MSA molecules emerge. These findings show that in the cold marine atmosphere MSA likely participates in atmospheric NPF.

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.

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.

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

We explored the hypothesis that on the nanoscale level, acids and bases might exhibit different behavior than in bulk solution. Our study system consisted of sulfuric acid, formic acid, ammonia, and water. We calculated highly accurate Domain-based Local pair-Natural Orbital- Coupled-Cluster/Complete Basis Set (DLPNO-CCSD(T)/CBS) energies on DFT geometries and used the resulting Gibbs free energies for cluster formation to compute the overall equilibrium constants for every possible cluster. The equilibrium constants combined with the initial monomer concentrations were used to predict the formation of clusters at the top and the bottom of the troposphere. Our results show that formic acid is as effective as ammonia at forming clusters with sulfuric acid and water. The structure of formic acid is uniquely suited to form hydrogen bonds with sulfuric acid. Additionally, it can partner with water to form bridges from one side of sulfuric acid to the other, hence demonstrating that hydrogen bonding topology is more important than acid/base strength in these atmospheric prenucleation clusters.

Modeling the Binding Free Energy of Large Atmospheric Sulfuric Acid-Ammonia Clusters

Sulfuric acid and ammonia are believed to account for a large fraction of new-particle formation in the atmosphere. However, it remains unclear how small clusters grow to larger sizes, eventually ending up as stable aerosol particles. Here we present the largest sulfuric acid-ammonia clusters studied to date using quantum chemical methods by calculating the binding free energies of (SA) _n (A) _n clusters, with n up to 20. Based on benchmark calculations, we apply the B97-3c//GFN1-xTB level of theory to calculate the cluster structures and thermochemical parameters. We find that the cluster structures drastically evolve at larger sizes. We identify that an ammonium ion is fully coordinated in the core of the cluster at n = 7, and at n = 13 we see the emergence of the first fully coordinated bisulfate ion. We identify multiple ammonium and bisulfate ions that are embedded in the core of the cluster structure at n = 19. The binding free energy per acid-base pair levels out around n = 8-10, indicating that at a certain point the thermochemistry of the clusters converges toward a constant value.

Monomers of Glycine and Serine Have a Limited Ability to Hydrate in the Atmosphere

The role of atmospheric aerosols on climate change is one of the biggest uncertainties in most global climate models. Organic aerosols have been identified as potential cloud condensation nuclei (CCN), and amino acids are organic molecules that could serve as CCN. Amino acids make up a significant portion of the total organic material in the atmosphere, and herein we present a systematic study of hydration for two of the most common atmospheric amino acids, glycine and serine. We compute DLPNO/CCSD(T)//M08-HX/MG3S thermodynamic properties and atmospheric concentrations of Gly(H₂O)_n and Ser(H₂O)_n, where n = 1-5. We predict that serine-water clusters have higher concentrations at n = 1 and 5, while glycine-water clusters have higher concentrations at n = 2-4. However, both glycine and serine are inferred to exist primarily in their nonhydrated monomer forms in the absence of other species such as sulfuric acid.

Tri-Base Synergy in Sulfuric Acid-Base Clusters

Synergistic effects between different bases can greatly enhance atmospheric sulfuric acid (SA)-base cluster formation. However, only the synergy between two base components has previously been investigated. Here, we extend this concept to three bases by studying large atmospherically relevant (SA)3(base)3 clusters, with the bases ammonia (A), methylamine (MA), dimethylamine (DMA), trimethylamine (TMA) and ethylenediamine (EDA). Using density functional theory—ωB97X-D/6-31++G(d,p)—we calculate the cluster structures and vibrational frequencies. The thermochemical parameters are calculated at 29,815 K and 1 atm, using the quasi-harmonic approximation. The binding energies of the clusters are calculated using high level DLPNO-CCSD(T0)/aug-cc-pVTZ. We find that the cluster stability in general depends on the basicity of the constituent bases, with some noteworthy additional guidelines: DMA enhances the cluster stability, TMA decreases the cluster stability and there is high synergy between DMA and EDA. Based on our calculations, we find it highly likely that three, or potentially more, different bases, are involved in the growth pathways of sulfuric acid-base clusters.

Integration of theory, simulation, artificial intelligence and virtual reality: a four-pillar approach for reconciling accuracy and interpretability in computational spectroscopy

The established pillars of computational spectroscopy are theory and computer based simulations. Recently, artificial intelligence and virtual reality are becoming the third and fourth pillars of an integrated strategy for the investigation of complex phenomena. The main goal of the present contribution is the description of some new perspectives for computational spectroscopy, in the framework of a strategy in which computational methodologies at the state of the art, high-performance computing, artificial intelligence and virtual reality tools are integrated with the aim of improving research throughput and achieving goals otherwise not possible. Some of the key tools (e.g., continuous molecular perception model and virtual multifrequency spectrometer) and theoretical developments (e.g., non-periodic boundaries, joint variational-perturbative models) are shortly sketched and their application illustrated by means of representative case studies taken from recent work by the authors. Some of the results presented are already well beyond the state of the art in the field of computational spectroscopy, thereby also providing a proof of concept for other research fields.

Thermodynamic properties of forming methanol-water and ethanol-water clusters at various temperatures and pressures and implications for atmospheric chemistry: A DFT study

The gas-phase geometries, binding energies, enthalpies, and free energies of methanol-(water)_n and ethanol-(water)_n clusters containing n=1-10,20,30,40, and 50 water molecules have been calculated using density functional theory. The binding energies are calculated at 0 K. The enthalpies are calculated at a temperature of 298.15 K and pressure of 1013.25 hPa (1 atm). The free energies are calculated at a wide range of temperature (T) and pressure (P) (from T = 298.15 K, P = 1013.25 hPa to T = 216.65 K, P = 226.32 hPa). The results show that the free energy of the formation of a specific cluster from its free molecules is negative (i.e., favorable) only below some critical temperature and pressure, which depends on the cluster's size. One of the most common volatile organic compounds (VOCs) in the troposphere is methanol, ethanol, and atmospheric aerosols containing methanol and ethanol. The Rayleigh scattering properties of methanol-water and ethanol-water clusters have been investigated. The scattering intensities were computed at static (∞ nm) and different wavelengths (700, 600, 500, and 400 nm) of naturally polarized light. Rayleigh scattering intensities increase about 9%-10% at 400 nm compared to the static limit (∞ nm) for both methanol-water and ethanol-water clusters.

New Particle Formation and Growth from Dimethyl Sulfide Oxidation by Hydroxyl Radicals

Dimethyl sulfide (DMS) is produced by plankton in oceans and constitutes the largest natural emission of sulfur to the atmosphere. In this work, we examine new particle formation from the primary pathway of oxidation of gas-phase DMS by OH radicals. We particularly focus on particle growth and mass yield as studied experimentally under dry conditions using the atmospheric simulation chamber AURA. Experimentally, we show that aerosol mass yields from oxidation of 50-200 ppb of DMS are low (2-7%) and that particle growth rates (8.2-24.4 nm/h) are comparable with ambient observations. An HR-ToF-AMS was calibrated using methanesulfonic acid (MSA) to account for fragments distributed across both the organic and sulfate fragmentation table. AMS-derived chemical compositions revealed that MSA was always more dominant than sulfate in the secondary aerosols formed. Modeling using the Aerosol Dynamics, gas- and particle-phase chemistry kinetic multilayer model for laboratory CHAMber studies (ADCHAM) indicates that the Master Chemical Mechanism gas-phase chemistry alone underestimates experimentally observed particle formation and that DMS multiphase and autoxidation chemistry is needed to explain observations. Based on quantum chemical calculations, we conclude that particle formation from DMS oxidation in the ambient atmosphere will most likely be driven by mixed sulfuric acid/MSA clusters clustering with both amines and ammonia.

Clusteromics I: Principles, Protocols, and Applications to Sulfuric Acid-Base Cluster Formation

We recently coined the term clusteromics as a holistic approach for obtaining insight into the chemical complexity of atmospheric molecular cluster formation and at the same time providing the foundation for thermochemical databases that can be utilized for developing machine learning models. Here, we present the first paper in the series that applies state-of-the-art computational methods to study multicomponent (SA)0-2(base)0-2 clusters, with SA = sulfuric acid and base = [ammonia (A), methylamine (MA), dimethylamine (DMA), trimethylamine (TMA), and ethylenediamine (EDA)] with all combinations of the five bases. The initial cluster configurations are obtained using the ABCluster program and the number of relevant configurations are reduced based on PM7 and ωB97X-D/6-31++G(d,p) calculations. Thermochemical parameters are calculated based on the ωB97X-D/6-31++G(d,p) cluster structures and vibrational frequencies using the quasi-harmonic approximation. The single-point energies are refined with a high-level DLPNO-CCSD(T0)/aug-cc-pVTZ calculation. Using the calculated thermochemical data, we perform kinetics simulations to evaluate the potential of these small (SA)0-2(base)0-2 clusters to grow into larger cluster sizes. In all cases we find that having more than one type of base molecule present in the cluster will increase the potential for forming larger clusters primarily due to the increased available vapor concentration.

Toward a Holistic Understanding of the Formation and Growth of Atmospheric Molecular Clusters: A Quantum Machine Learning Perspective

The formation of atmospheric molecular clusters is an important stage in forming new particles in the atmosphere. Despite being a highly focused research area, the exact chemical species involved in the initial steps in new particle formation remain elusive. In this Perspective the main challenges and recent progression in the field are outlined with a special emphasis on the chemical complexity of the puzzle and prospect of modeling larger clusters. In general, there is a high demand for accurate and more complete quantum chemical data sets that can be applied in cluster distribution dynamics models and coupled to atmospheric chemical transport models. A view on how the community could reach this goal by applying data-driven machine learning approaches for more efficient exploration of cluster configurations is presented. A path toward larger clusters and direct molecular dynamics simulations of cluster formation and growth using machine learning models is discussed.

Towards a converged strategy for including microsolvation in reaction mechanism calculations

A major part of chemical conversions is carried out in the fluid phase, where an accurate modeling of the involved reactions requires to also take into account solvation effects. Implicit solvation models often cover these effects with sufficient accuracy but can fail drastically when specific solvent-solute interactions are important. In those cases, microsolvation, i.e., the explicit inclusion of one or more solvent molecules, is a commonly used strategy. Nevertheless, microsolvation also introduces new challenges-a consistent workflow as well as strategies how to systematically improve prediction performance are not evident. For the COSMO and COSMO-RS solvation models, this work proposes a simple protocol to decide if microsolvation is needed and how the corresponding molecular model has to look like. To demonstrate the improved accuracy of the approach, specific application examples are presented and discussed, i.e., the computation of aqueous pK_a values and a mechanistic study of the methanol mediated Morita-Baylis-Hillman reaction.

Hydration motifs of ammonium bisulfate clusters show complex temperature dependence

The role of water in the formation of particles from atmospheric trace gases is not well understood, in large part due to difficulties in detecting its presence under atmospheric conditions and the variety of possible structures that must be screened computationally. Here, we use infrared spectroscopy and variable-temperature ion trap mass spectrometry to investigate the structural motifs adopted by water bound to ammonium bisulfate clusters and their temperature dependence. For clusters featuring only acid-base linkages, water adopts a bridging arrangement spanning an adjacent ammonium and bisulfate. For larger clusters, water can also insert into a bisulfate-bisulfate hydrogen bond, yielding hydration isomers with very similar binding energies. The population of these isomers shows a complex temperature evolution, as an apparent third isomer appears with a temperature dependence that is difficult to explain using simple thermodynamic arguments. These observations suggest that the thermodynamics of water binding to atmospheric clusters such as these may not be straightforward.

Establishing the structural motifs present in small ammonium and aminium bisulfate clusters of relevance to atmospheric new particle formation

Atmospheric new particle formation is the process by which atmospheric trace gases, typically acids and bases, cluster and grow into potentially climatically relevant particles. Here, we evaluate the structures and structural motifs present in small cationic ammonium and aminium bisulfate clusters that have been studied both experimentally and computationally as seeds for new particles. For several previously studied clusters, multiple different minimum-energy structures have been predicted. Vibrational spectra of mass-selected clusters and quantum chemical calculations allow us to assign the minimum-energy structure for the smallest cationic cluster of two ammonium ions and one bisulfate ion to a C_S-symmetry structure that is persistent under amine substitution. We derive phenomenological vibrational frequency scaling factors for key bisulfate vibrations to aid in the comparison of experimental and computed spectra of larger clusters. Finally, we identify a previously unassigned spectral marker for intermolecular bisulfate-bisulfate hydrogen bonds and show that it is present in a class of structures that are all lower in energy than any previously reported structure. Tracking this marker suggests that this motif is prominent in larger clusters as well as ∼180 nm ammonium bisulfate particles. Taken together, these results establish a set of structural motifs responsible for binding of gases at the surface of growing clusters that fully explain the spectrum of large particles and provide benchmarks for efforts to improve structure predictions, which are critical for the accurate theoretical treatment of this process.

Impact of Quantum Chemistry Parameter Choices and Cluster Distribution Model Settings on Modeled Atmospheric Particle Formation Rates

We tested the influence of various parameters on the new particle formation rate predicted for the sulfuric acid-ammonia system using quantum chemistry and cluster distribution dynamics simulations, in our case, Atmospheric Cluster Dynamics Code (ACDC). We found that consistent consideration of the rotational symmetry number of monomers (sulfuric acid and ammonia molecules, and bisulfate and ammonium ions) leads to a significant rise in the predicted particle formation rate, whereas inclusion of the rotational symmetry number of the clusters only changes the results slightly, and only in conditions where charged clusters dominate the particle formation rate. This is because most of the clusters stable enough to participate in new particle formation have a rotational symmetry number of 1, and few exceptions to this rule are positively charged clusters. In contrast, the application of the quasi-harmonic correction for low-frequency vibrational modes tends to generally decrease predicted new particle formation rates and also significantly alters the slope of the formation rate curve plotted against the sulfuric acid concentration, which is a typical convention in atmospheric aerosol science. The impact of the maximum size of the clusters explicitly included in the simulations depends on the simulated conditions. The errors arising from a limited set of clusters are higher for higher evaporation rates, and thus tend to increase with temperature. Similarly, the errors tend to be higher for lower vapor concentrations. The boundary conditions for outgrowing clusters (that are counted as formed particles) have only a small influence on the results, provided that the definition is chemically reasonable and that the set of simulated clusters is sufficiently large. A comparison with data from the Cosmics Leaving OUtdoor Droplets (CLOUD) chamber and a cluster distribution dynamics model using older quantum chemistry input data shows improved agreement when using our new input data and the proposed combination of symmetry and quasi-harmonic corrections.

2-Methyltetrol sulfate ester-initiated nucleation mechanism enhanced by common nucleation precursors: A theory study

Aerosol samples from all over the word contained 2-methyltetrol sulfate ester (MTS). We investigated the role of MTS in new particle formation (NPF) with aerosol nucleation precursors, including sulfuric acid (SA), water (W), ammonia (N), methylamine (MA), dimethylamine (DMA), and trimethylamine (TMA). The analysis was performed using quantum chemical approach, kinetic calculation and molecular dynamics (MD) simulations. The results proved that the molecular interactions in the clusters were mainly H-bonds and electrostatic interaction. The negative Gibbs free energy changes for all the studied MTS-containing clusters indicated that the formation of these clusters was thermodynamically favorable. The stability of the clusters was evaluated according to the total evaporation rate. Here, (MTS)(SA) and (MTS)(W) were the most and least stable cluster, respectively. MD simulations were used for time and spatial analysis of the role of the MTS-SA system. The results indicated that MTS can self-aggregate or absorb SA molecules into clusters, larger than the size of the critical cluster (approximately 1 nm), suggesting that MTS can initiate NPF by itself or together with SA.

Neutral Sulfuric Acid-Water Clustering Rates: Bridging the Gap between Molecular Simulation and Experiment

The role of sulfuric acid during atmospheric new particle formation is an ongoing topic of discussion. In this work, we provide quantitative experimental constraints for quantum chemically calculated evaporation rates for the smallest H₂SO₄-H₂O clusters, characterizing the mechanism governing nucleation on a kinetic, single-molecule level. We compare experimental particle size distributions resulting from a highly supersaturated homogeneous H₂SO₄ gas phase with the results from kinetic simulations employing quantum chemically derived decomposition rates of electrically neutral H₂SO₄ molecular clusters up to the pentamer at a large range of relative humidities. By using high H₂SO₄ concentrations, we circumvent the uncertainties concerning contaminants and competing reactions present in studies at atmospheric conditions. We show good agreement between molecular simulation and experimental measurements and provide the first evaluation of theoretical predictions of the stabilization provided by water molecules.

The unexpected effect of aqueous ion pairs on the forbidden n →π* transition in nitrate

Aqueous nitrate is ubiquitous in the environment, found for example in stratospheric clouds, tropospheric particulate matter, rain and snow, fertilized fields, rivers and the ocean. Its photolysis is initiated by absorption into the strongly forbidden n →π* transition. Photolysis reactivates deposited nitrate, releasing nitrogen oxides, and UV light is commonly used to break down nitrate pollution. The transition is doubly forbidden unless its symmetry is broken, giving a powerful means of probing the interactions of nitrate with its environment and of using experiment to validate the results of theory. In this study we demonstrate the remarkably different effects of the addition of a series of mono- and di-valent metal chlorides on the nitrate UV transition. While they all shift the transition to shorter wavelengths, the shift changes significantly from one to another. For the monovalent series Li⁺, Na⁺, K⁺, the blue shift decreases down the column being strongest for Li⁺ and weakest for K⁺. For the divalent series Mg²⁺, Ca²⁺, Ba²⁺, the opposite effect is observed with the energy shift of Ba²⁺ being an order of magnitude larger than for Mg²⁺. The absorption intensity also changes; the addition of Na⁺ and K⁺ decrease intensity whereas Li⁺ increases intensity. For the divalent cations an increase is seen for all three members of the series Mg²⁺, Ca²⁺ and Ba²⁺. Paradoxically, the effect of addition of CaCl₂ to the solution is to decrease the environmental photolysis rate of nitrate; despite the increase in intensity, Ca²⁺ blue shifts the peak position above the tropospheric photolysis threshold around 300 nm. Using computational chemistry we conclude that the effects are due to the microscopic interactions of the nitrate anion and not continuum effects. Two microscopic mechanisms are investigated in detail, the formation of a nitrate monohydrate cluster and a contact ion pair. The contact ion pair shows the potential for significant impact on the energy and intensity of the transition.

Systematic microsolvation approach with a cluster-continuum scheme and conformational sampling

Solvation is a notoriously difficult and nagging problem for the rigorous theoretical description of chemistry in the liquid phase. Successes and failures of various approaches ranging from implicit solvation modeling through dielectric continuum embedding and microsolvated quantum chemical modeling to explicit molecular dynamics highlight this situation. Here, we focus on quantum chemical microsolvation and discuss an explicit conformational sampling ansatz to make this approach systematic. For this purpose, we introduce an algorithm for rolling and automated microsolvation of solutes. Our protocol takes conformational sampling and rearrangements in the solvent shell into account. Its reliability is assessed by monitoring the evolution of the spread and average of the observables of interest.

Strong Even/Odd Pattern in the Computed Gas-Phase Stability of Dicarboxylic Acid Dimers: Implications for Condensation Thermodynamics

The physical properties of small straight-chain dicarboxylic acids are well known to exhibit even/odd alternations with respect to the carbon chain length. For example, odd numbered diacids have lower melting points and higher saturation vapor pressures than adjacent even numbered diacids. This alternation has previously been explained in terms of solid-state properties, such as higher torsional strain of odd number diacids. Using quantum chemical methods, we demonstrate an additional contribution to this alternation in properties resulting from gas-phase dimer formation. Due to a combination of hydrogen bond strength and torsional strain, dimer formation in the gas phase occurs efficiently for glutaric acid (C5) and pimelic acid (C7) but is unfavorable for succinic acid (C4) and adipic acid (C6). Our results indicate that a significant fraction of the total atmospheric gas-phase concentration of glutaric and pimelic acid may consist of dimers.

Electrospray Ionization-Based Synthesis and Validation of Amine-Sulfuric Acid Clusters of Relevance to Atmospheric New Particle Formation

Atmospheric new particle formation (NPF) is the process by which atmospheric trace gases such as sulfuric acid, ammonia, and amines cluster and grow into climatically relevant particles. The mechanism by which these particles form and grow has remained unclear, in large part due to difficulties in obtaining molecular-level information about the clusters as they grow. Mass spectrometry-based methods using electrospray ionization (ESI) as a cluster source have shed light on this process, but the produced cluster distributions have not been rigorously validated against experiments performed in atmospheric conditions. Ionic clusters are produced by ESI of solutions containing the amine and bisulfate or by spraying a sulfuric acid solution and introducing trace amounts of amine gas into the ESI environment. The amine content of clusters can be altered by increasing the amount of amine introduced into the ESI environment, and certain cluster compositions can only be made by the vapor exchange method. Both approaches are found to yield clusters with the same structures. Aminium bisulfate cluster distributions produced in a controlled and isolated ESI environment can be optimized to closely resemble those observed by chemical ionization in the CLOUD chamber at CERN. These studies indicate that clusters generated by ESI are also observed in traditional atmospheric measurements, which puts ESI mass spectrometry-based studies on firmer footing and broadens the scope of traditional mass spectrometry experiments that may be applied to NPF.

Configurational Sampling of Noncovalent (Atmospheric) Molecular Clusters: Sulfuric Acid and Guanidine

We studied the configurational sampling of noncovalently bonded molecular clusters relevant to the atmosphere. In this article, we discuss possible approaches to searching for optimal configurations and present one alternative based on systematic configurational sampling, which seems able to overcome the typical problems associated with searching for global minima on multidimensional potential energy surfaces. Since atmospheric molecular clusters are usually held together by intermolecular bonds, we also present a cost-effective strategy for treating hydrogen bonding and proton transferring by using rigid molecules and ions in different protonation states and illustrate its performance on clusters containing guanidine and sulfuric acid.

The reaction of hydrated iodide I(H2O)− with ozone: a new route to IO2− products

We report on an experimental characterization of the isolated reaction of hydrated iodide I(H₂O)⁻ with ozone O₃ at room temperature performed using a radio-frequency ion trap combined with a quadrupole mass spectrometer.

Benchmarking sampling methodology for calculations of Rayleigh light scattering properties of atmospheric molecular clusters

We present four different computational methods for benchmarking the sampling and Rayleigh light scattering of hydrogen bonded atmospheric molecular clusters.

Hydration motifs of ammonium bisulfate clusters of relevance to atmospheric new particle formation

We have analyzed the binding motifs of water bound to a prototypical cluster containing three ammonium cations and two bisulfate anions using mass-selective vibrational spectroscopy and quantum chemical calculations.

Direct Link between Structure and Hydration in Ammonium and Aminium Bisulfate Clusters Implicated in Atmospheric New Particle Formation

The acid-base chemistry of amines and sulfuric acid promotes growth in the early stages of atmospheric new particle formation, with more basic amines enhancing growth rates. Hydration of these particles has been proposed to depend on acidity or basicity but is difficult to quantify; therefore, the role of water in this process is not well understood. Using tandem mass spectrometry coupled to a temperature-controlled ion trap, we show that water uptake by aminium bisulfate clusters depends on the total number of free hydrogen bond donors in the cluster and is unaffected by the interchange of amines featuring the same number of substituents but differing gas-phase basicity. Analyzing this trend reveals site-specific propensities for hydration. These results indicate that hydration is determined by structural factors and that reported dependences on acidity or basicity arise from the weaker correlation between the number of hydrogen bond donors of amines and their gas-phase basicity.