First-Principles Study of Molecular Clusters Formed by Nitric Acid and Ammonia

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.

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.

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.

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.

Formation Mechanisms of Iodine-Ammonia Clusters in Polluted Coastal Areas Unveiled by Thermodynamics and Kinetic Simulations

It has been revealed that iodine species play important roles in atmospheric new particle formations (NPFs) in pristine coastal areas. However, it is unclear whether other atmospheric species, such as NH₃, for which the levels in coastal areas of China are >2.5 × 10¹⁰ molecules·cm^-3 are involved in the NPFs of iodine species, although NH₃ has been proved to promote particle formation of H₂SO₄. Via high-level quantum chemical calculations and atmospheric cluster dynamic code simulations, this study unveiled new mechanisms of nucleation, in which NH₃ mediates the formation of iodine particles by assisting hydrolysis of I₂O₅ or reacting with HIO₃. The simulated formation rates of iodine-ammonia clusters via the new mechanisms are much higher than those simulated via sequential addition of HIO₃ with subsequent release of H₂O, under the condition that NH₃ concentrations are higher than 10¹⁰ molecules·cm^-3. The new mechanisms can well explain the observed cluster formation rates at a coastal site in Zhejiang of China. The findings not only expand the current understandings of the role of NH₃ in NPFs but also highlight the importance of monitoring and evaluating NPFs via the iodine-ammonia cluster pathway in the coastal areas of China and other regions worldwide.

NWPEsSe: An Adaptive-Learning Global Optimization Algorithm for Nanosized Cluster Systems

Global optimization constitutes an important and fundamental problem in theoretical studies in many chemical fields, such as catalysis, materials, or separations problems. In this paper, a novel algorithm has been developed for the global optimization of large systems including neat and ligated clusters in the gas phase and supported clusters in periodic boundary conditions. The method is based on an updated artificial bee colony (ABC) algorithm method, that allows for adaptive-learning during the search process. The new algorithm is tested against four classes of systems of diverse chemical nature: gas phase Au₅₅, ligated Au₈²⁺, Au₈ supported on graphene oxide and defected rutile, and a large cluster assembly [Co₆Te₈(PEt₃)₆][C₆₀]_n, with sizes ranging between 1 and 3 nm and containing up to 1300 atoms. Reliable global minima (GMs) are obtained for all cases, either confirming published data or reporting new lower energy structures. The algorithm and interface to other codes in the form of an independent program, Northwest Potential Energy Search Engine (NWPEsSe), is freely available, and it provides a powerful and efficient approach for global optimization of nanosized cluster systems.

Atmospheric implication of synergy in methanesulfonic acid–base trimers: a theoretical investigation

Synergy between molecules is ubiquitous in atmospheric clusters and significantly affects new particle formation (NPF). Herein, the effects of the synergy between base molecules on the stability and evaporation of MSA–X–Y (MSA = methanesulfonic acid; X, Y = ammonia (A), methylamine (M), or dimethylamine (D)) trimers were investigated via density functional theory (DFT) and the atmospheric clusters dynamic code (ACDC) method. The results show that proton transfer from MSA to X is exothermal and barrierless due to the synergy between X and Y molecules in MSA–X–Y trimers compared with MSA-X dimers. Cyclic hydrogen bonds are a typical characteristic of the stable trimers. Topological analysis using atoms in molecules (AIM) theory indicates that the electron density (ρ) and Laplacian of the electron density (∇²ρ) at the bond critical points (BCPs) in the trimers exceed the standard range of hydrogen bonds. The affinity for attaching a Y molecule to the MSA–X dimers and the substitution of Y₁ (Y = A and MA) by Y₂ (Y₂ = MA and DMA) in the MSA–X–Y trimers are thermodynamically spontaneous. In addition, the cyclic stabilization energy of the MSA–X–Y trimers increased as the alkalinities of X and Y increased. The total evaporation rate of the trimers decreased as the alkalinities of X and Y increased. Low temperature and high pressure significantly facilitate the formation of trimers. It is further confirmed that synergy plays an important role in atmospheric NPF events.

The effects of synergy of between X and Y on the stability of MSA–X–Y trimers were investigated via quantum chemical and kinetics simulation method.

Piperazine Enhancing Sulfuric Acid-Based New Particle Formation: Implications for the Atmospheric Fate of Piperazine

Piperazine (PZ), a cyclic diamine, is one of 160 detected atmospheric amines and an alternative solvent to the widely used monoethanolamine in post-combustion CO₂ capture. Participating in H₂SO₄ (sulfuric acid, SA)-based new particle formation (NPF) could be an important removal pathway for PZ. Here, we employed quantum chemical calculations and kinetics modeling to evaluate the enhancing potential of PZ on SA-based NPF by examining the formation of PZ-SA clusters. The results indicate that PZ behaves more like a monoamine in stabilizing SA and can enhance SA-based NPF at the parts per trillion (ppt) level. The enhancing potential of PZ is less than that of the chainlike diamine putrescine and greater than that of dimethylamine, which is one of the strongest enhancing agents confirmed by ambient observations and experiments. After the initial formation of the (PZ)₁(SA)₁ cluster, the cluster mainly grows by gradual addition of SA or PZ monomer, followed by addition of (PZ)₁(SA)₁ cluster. We find that the ratio of PZ removal by NPF to that by the combination of NPF and oxidations is 0.5-0.97 at 278.15 K. As a result, we conclude that participation in the NPF pathway could significantly alter the environmental impact of PZ compared to only considering oxidation pathways.

The role of nitric acid in atmospheric new particle formation

Nitric acid, an air pollutant with strong acidity and oxidizability, can be found in considerable quantities in the gas and aerosol phase. Understanding the role of nitric acid in atmospheric new particle formation is essential to study the complicated nucleation mechanism. Using density functional theory combined with the Atmospheric Clusters Dynamic Code (ACDC), the role of nitric acid in the formation of new particles has been investigated under different atmospheric conditions (different precursor concentrations and temperatures). The results show that nitric acid can form clusters with sulfuric acid and ammonia by hydrogen bond or even proton-transfer interactions. The concentrations of clusters involving nitric acid can be comparable with those of sulfuric acid-ammonia-based clusters, considering the thermodynamic stability combined with the realistic atmospheric concentrations of precursors. Within the atmospheric concentration range, nitric acid can enhance the formation rates of sulfuric acid-ammonia clusters, especially at low temperature, low sulfuric acid concentration and high ammonia concentration. In addition, the new particle formation mechanism indicates that nitric acid can contribute to the cluster formation and the role of nitric acid in the cluster formation pathway is as a "bridge" connecting the smaller and larger clusters.

Atmospheric Fate of Monoethanolamine: Enhancing New Particle Formation of Sulfuric Acid as an Important Removal Process

Monoethanolamine (MEA), a potential atmospheric pollutant from the capture unit of a leading CO₂ capture technology, could be removed by participating H₂SO₄-based new particle formation (NPF) as simple amines. Here we evaluated the enhancing potential of MEA on H₂SO₄-based NPF by examining the formation of molecular clusters of MEA and H₂SO₄ using combined quantum chemistry calculations and kinetics modeling. The results indicate that MEA at the parts per trillion (ppt) level can enhance H₂SO₄-based NPF. The enhancing potential of MEA is less than that of dimethylamine (DMA), one of the strongest enhancing agents, and much greater than methylamine (MA), in contrast to the order suggested solely by their basicity (MEA < MA < DMA). The unexpectedly high enhancing potential is attributed to the role of -OH of MEA in increasing cluster binding free energies by acting as both a hydrogen bond donor and acceptor. After the initial formation of one H₂SO₄ and one MEA cluster, the cluster growth mainly proceeds by first adding one H₂SO₄, and then one MEA, which differs from growth pathways in H₂SO₄-DMA and H₂SO₄-MA systems. Importantly, the effective removal rate of MEA due to participation in NPF is comparable to that of oxidation by hydroxyl radicals at 278.15 K, indicating NPF as an important sink for MEA.