| 24 Jun 2026
Role of Methanesulfonic Acid in Freshly Nucleated Particle Formation and Growth
Abstract. Sulfuric acid (SA) together with base molecules such as ammonia (AM), methylamine (MA) and dimethylamine (DMA) is known to play a central role in atmospheric new particle formation (NPF). NPF occurs through gas-to-particle conversion via the formation and growth of molecular clusters. While previous studies have demonstrated that mixtures of bases can strongly enhance nucleation rates, the influence of multiple acidic species for larger cluster stability and growth remains less explored.
In this work, we investigate the role of mixed-acid systems in atmospheric cluster formation using quantum chemical calculations, assisted by machine-learning. Cluster structures containing SA, methane sulfonic acid (MSA), and atmospherically relevant bases (AM, MA, and DMA), with compositions up to 10 acid–base pairs, were generated through extensive configurational sampling using ABCluster and metadynamics simulations with CREST. The resulting structures were subsequently optimized at the B97-3c level of theory, while a PaiNN machine-learning model was used to accelerate the calculation.
Our results show that, in contrast to previously reported base synergy, the acid synergy between SA and MSA is weak and highly system dependent. SA consistently dominates the thermodynamic stability of the smallest clusters, and MSA-only acid–base interactions are insufficient to explain efficient initial particle formation. In particular, for systems involving DMA, the strong SA–DMA interaction governs the cluster energetics, with little contribution of MSA to the stability. However, MSA can influence cluster stability at larger sizes in systems involving weaker bases such as AM and MA, especially under conditions where the relative abundance of MSA is high. These findings indicate that MSA does not act as a primary nucleating acid, but rather as a secondary species that participate in the early growth of clusters.
Overall, this work highlights that the roles of different atmospheric acids in NPF are fundamentally distinct: SA controls the initial nucleation step, whereas MSA may enhance subsequent cluster growth under specific atmospheric conditions.
Competing interests: At least one of the (co-)authors is a member of the editorial board of Aerosol Research.
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This manuscript presents a computational investigation of large neutral clusters containing sulfuric acid (SA), methanesulfonic acid (MSA), and amine bases (AM, MA, DMA), extending the cluster size up to 10 acid–base pairs (20 molecules). The study addresses an important topic in aerosol formation, and the reported structural and thermochemical data for large mixed-acid clusters could constitute a valuable contribution to the field, consistent with the scope of Aerosol Research. The manuscript addresses a timely and interesting topic, and the generation of large-cluster data is potentially valuable. However, the current version has substantial gaps in literature coverage, compositional sampling and data accessibility. A major revision is required to address these points. After thorough revision and careful technical editing, the manuscript could become a worthy contribution to Aerosol Research.
Major Comments
Technical Corrections
Abstract, line 7: “methane sulfonic acid” → “methanesulfonic acid”.
Abstract, line 16: “a secondary species that participate” → “a secondary species that participates”.
Line 41: “2nm” → “2 nm”.
Line 43: “around ∼1.5 nm” – use either “around 1.5 nm” or “∼1.5 nm” (redundant).
Lines 47–48: Add parentheses before and after “Almeida et al. (2013)” and clarify whether “ten acid and base molecules” means ten molecules total or ten acid–base pairs.
Line 57: “marine environment” → “marine environments”.
Line 83: “up to n=10 acid-base molecules” → “up to n=10 acid–base pairs (20 molecules)”.
Lines 97–98: Revise “clusters of 1 to n=5” for clarity (e.g., “clusters with n = 1 to 5”).
Line 102: “improves finding global minimum” → “improves the likelihood of finding the global minimum”; use “global minima” when referring to several clusters.
Line 120: “as implement in SchNetPack” → “as implemented in SchNetPack”.
Lines 122–124: “model to performed excellently” → “model to perform well”; “structures ... was used” → “structures ... were used”.
Line 132: “as following” → “as follows”.
Line 145: “Equation (1) ... describe” → “describes”; remove the comma in “with a 100 cm⁻¹, threshold”.
Line 158: “as a function of molecules in the cluster” → “as a function of the number of molecules in the cluster”.
Lines 169–171 and throughout: Standardise spacing in kcal mol⁻¹ and all units (e.g., use non‑breaking thin spaces where appropriate).
Line 222: “MSA only affect” → “MSA only affects”.
Line 231: Remove “the” from “the our calculations”.
Figure 4: Reconcile 298Lmsa in the panels with 298Hmsa in the caption/text.
Line 246: “we see now role of MSA” – ambiguous; revise for clarity (likely a typo).
Line 252: “the DMA-containing cluster remain” → “clusters remain” (or “the DMA-containing clusters remain”).
Section 3.2.4 heading: Standardise capitalization and spacing in “High MSA–high SA”.
Figure 7 caption: Remove the comma in “molec., cm⁻³” and use “molecules cm⁻³” consistently.
Data availability: Replace the ACDB root link with a direct, versioned dataset link and citation.
References: Kirkby et al. (2011a, 2011b) appear to duplicate the same Nature article; Nadykto et al. (2014a, 2014b) also appear duplicated. Remove duplicates and retain single entries.
References: Cooley et al. (2023) and Cromar and Lazrak (2023) lack complete bibliographic information (e.g., volume, page numbers, or DOI); provide full details.