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

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.

Stability and Structure of Potentially Atmospherically Relevant Glycine Ammonium Bisulfate Clusters

New particle formation (NPF) is the process by which trace atmospheric acids and bases cluster and grow into particles that ultimately impact climate. Sulfuric acid concentration drives NPF, but nitrogen-containing bases promote the formation of more stable clusters via salt bridge formation. Recent computational efforts have suggested that amino acids can enhance NPF, predicting that they can stabilize new particles via multiple protonation sites, but there has yet to be experimental validation of these predictions. We used mass spectrometry and infrared spectroscopy to study the structure and stability of cationic clusters composed of glycine, sulfuric acid, and ammonia. When collisionally activated, clusters were significantly more likely to eliminate ammonia or sulfuric acid than glycine, while quantum chemical calculations predicted lower binding free energies for ammonia but similar binding free energies for glycine and sulfuric acid. These calculations predicted several low-energy structures, so we compared experimental and computed vibrational spectra to attempt to validate the computationally predicted minimum energy structure. Unambiguous identification of the experimental structure by comparison to these calculations was made difficult by the complexity of the experimental spectra and the fact that the identity of the computed lowest-energy structure depended strongly on temperature. If their vapors are present, amino acids are likely to be enriched in new particles by displacing more weakly bound ammonia, similar to the behavior of other atmospheric amines. The carboxylic acid groups were found to preferentially interact with other carboxylic acids, suggesting incipient organic/inorganic phase separation even at these small sizes.

Prebiotic dimer and trimer peptide formation in gas-phase atmospheric nanoclusters of water

Insight into the origin of prebiotic molecules is key to our understanding of how living systems evolved into the complex network of biological processes on Earth. By modelling diglycine and triglycine peptide formation in the prebiotic atmosphere, we provide a plausible pathway for peptide growth. By examining different transition states (TSs), we conclude that the formation of diglycine and triglycine in atmospheric nanoclusters of water in the prebiotic atmosphere kinetically favors peptide growth by an N-to-C synthesis of glycines through a trans conformation. Addition of water stabilizes the TS structures and lowers the Gibbs free activation energies. At temperatures that model the prebiotic atmosphere, the free energies of activation with a six water nanocluster as part of the TS are predicted to be 16 kcal mol-1 relative to the prereactive complex. Examination of the trans vs. cis six water transition states reveals that a homodromic water network that maximizes the acceptor/donor nature of the six waters is responsible for enhanced kinetic favorability of the trans N-to-C pathway. Compared to the non-hydrated trans TS, the trans six-water TS accelerates the reaction of diglycine and glycine to form triglycine by 13 orders of magnitude at 217 K. Nature uses the trans N-to-C pathway to synthesize proteins in the ribosome, and we note the similarities in hydrogen bond stabilization between the transition state for peptide synthesis in the ribosome and the transition states formed in nanoclusters of water in the same pathway. These results support the hypothesis that small oligomers formed in the prebiotic atmosphere and rained onto earth's surface.

Revealing the Impacts of Chemical Complexity on Submicrometer Sea Spray Aerosol Morphology

Sea spray aerosol (SSA) ejected through bursting bubbles at the ocean surface is a complex mixture of salts and organic species. Submicrometer SSA particles have long atmospheric lifetimes and play a critical role in the climate system. Composition impacts their ability to form marine clouds, yet their cloud-forming potential is difficult to study due to their small size. Here, we use large-scale molecular dynamics (MD) simulations as a "computational microscope" to provide never-before-seen views of 40 nm model aerosol particles and their molecular morphologies. We investigate how increasing chemical complexity impacts the distribution of organic material throughout individual particles for a range of organic constituents with varying chemical properties. Our simulations show that common organic marine surfactants readily partition between both the surface and interior of the aerosol, indicating that nascent SSA may be more heterogeneous than traditional morphological models suggest. We support our computational observations of SSA surface heterogeneity with Brewster angle microscopy on model interfaces. These observations indicate that increased chemical complexity in submicrometer SSA leads to a reduced surface coverage by marine organics, which may facilitate water uptake in the atmosphere. Our work thus establishes large-scale MD simulations as a novel technique for interrogating aerosols at the single-particle level.

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.

Computational chemistry of cluster: Understanding the mechanism of atmospheric new particle formation at the molecular level

New particle formation (NPF), which exerts significant influence over human health and global climate, has been a hot topic and rapidly expands field of research in the environmental and atmospheric chemistry recent years. Generally, NPF contains two processes: formation of critical nucleus and further growth of the nucleus. However, due to the complexity of the atmospheric nucleation, which is a multicomponent process, formation of critical clusters as well as their growth is still connected to large uncertainties. Detection limits of instruments in measuring specific gaseous aerosol precursors and chemical compositions at the molecular level call for computational studies. Computational chemistry could effectively compensate the deficiency of laboratory experiments as well as observations and predict the nucleation mechanisms. We review the present theoretical literatures that discuss nucleation mechanism of atmospheric clusters. Focus of this review is on different nucleation systems involving sulfur-containing species, nitrogen-containing species and iodine-containing species. We hope this review will provide a deep insight for the molecular interaction of nucleation precursors and reveal nucleation mechanism at the molecular level.

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.