Improved Configurational Sampling Protocol for Large Atmospheric Molecular Clusters.

Area of Science:

• Atmospheric chemistry
• Computational chemistry
• Aerosol science

Background:

• Atmospheric particle formation is crucial for aerosol research.
• Quantum chemical calculations model early-stage aerosol formation.
• Balancing accuracy and computational cost is key for large systems.

Purpose of the Study:

• Benchmark computational methods for large atmospheric clusters.
• Improve configurational sampling for accurate global energy minimum searches.
• Investigate low-energy configurations of sulfuric acid-amine clusters.

Main Methods:

• Benchmarking B97-3c method for binding energies and structures.
• Developing and assessing a funneling approach for configurational sampling.
• Applying the workflow to sulfuric acid-ammonia and sulfuric acid-dimethylamine clusters.

Main Results:

• B97-3c offers a balance of accuracy and computational cost for large clusters.
• The funneling approach enhances accuracy in finding global energy minima.
• Dimethylamine-containing clusters exhibit greater binding free energy stability than ammonia-containing clusters.

Conclusions:

• The developed methodology bridges computational and experimental scales in aerosol research.
• The funneling approach improves the study of large molecular clusters.
• Dimethylamine is a more effective stabilizing agent than ammonia in these clusters.