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Updated: Nov 11, 2025
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Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry
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Clusteromics I: Principles, Protocols, and Applications to Sulfuric Acid-Base Cluster Formation
1Department of Chemistry and iClimate, Aarhus University, 8000 Aarhus C, Denmark.
ACS Omega
|March 29, 2021
Summary
Clusteromics reveals how atmospheric clusters form. Multiple base molecules, like ammonia and amines, significantly enhance cluster growth by increasing vapor concentration, aiding climate models.
Area of Science:
- Atmospheric Chemistry
- Computational Chemistry
- Chemical Physics
Background:
- Atmospheric molecular clusters influence climate and air quality.
- Understanding cluster formation is crucial for climate modeling.
- Existing models lack comprehensive data on multicomponent clusters.
Purpose of the Study:
- Introduce 'clusteromics' for studying atmospheric cluster formation.
- Investigate multicomponent clusters of sulfuric acid and various bases.
- Provide thermochemical data for machine learning model development.
Main Methods:
- Utilized ABCluster for initial configurations.
- Employed PM7 and ωB97X-D/6-31++G(d,p) for configuration reduction.
- Calculated thermochemical parameters using ωB97X-D/6-31++G(d,p) and DLPNO-CCSD(T0)/aug-cc-pVTZ.
- Performed kinetics simulations for cluster growth potential.
Main Results:
- Studied clusters of sulfuric acid with ammonia, methylamine, dimethylamine, trimethylamine, and ethylenediamine.
- Calculated thermochemical parameters for various multicomponent clusters.
- Kinetics simulations showed increased growth potential with multiple base types.
Conclusions:
- Multicomponent clusters, especially with multiple bases, enhance cluster growth.
- Increased vapor concentration from multiple bases drives larger cluster formation.
- This work lays the foundation for improved atmospheric models and machine learning applications.
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