Computer Generated Realistic Interstellar Icy Grain Models: Physicochemical Properties and Interaction with NH₃.

Area of Science:

• Astrochemistry and Computational Astrophysics
• Materials Science of Ices
• Quantum Chemistry

Background:

• Interstellar grains, essential for forming complex organic molecules (iCOMs), consist of silicate cores with icy mantles (H2O, CO, CO2, NH3).
• Existing models lack systematic studies on crucial grain properties like H-bonds, radial distribution, and surface electrostatics.
• Understanding these properties is vital for accurately modeling chemical evolution in dense molecular clouds.

Purpose of the Study:

• To develop a computational procedure (ACO-FROST) for building large, realistic amorphous ice structures mimicking interstellar grains.
• To enable systematic studies of adsorption properties on various sites of these icy grain models.
• To provide statistically meaningful physicochemical data for astrochemical numerical models.

Main Methods:

• Utilized the semiempirical GFN2 tight-binding quantum mechanical method and the GFN-FF force field for accurate and cost-effective simulations.
• Developed the ACO-FROST program to construct large-scale amorphous ice structures, tunable for different compositions (e.g., dirty icy grains).
• Calculated adsorption features including binding energy, and vibrational frequencies for species on the simulated grain surfaces.

Main Results:

• Successfully generated large amorphous ice structures with a favorable accuracy/cost ratio, suitable for studying noncovalent interactions.
• Demonstrated the ability to model 'dirty' icy grains with varying compositions.
• Computed the binding energy of ammonia on the icy grain surface, revealing a broad distribution not captured by smaller models.

Conclusions:

• ACO-FROST provides a robust method for creating realistic interstellar icy grain models, enabling detailed adsorption studies.
• The method yields statistically significant data on adsorption properties, improving astrochemical models.
• This work lays the foundation for more rigorous QM:MM treatments to achieve chemical accuracy in binding energy calculations.