The Nucleated Atomistic Grain Growth Simulator (NAGGS): application to the size-dependent structural and physical properties of nanosilicate dust

TL;DR

The paper introduces NAGGS, a new atomistic simulation tool for modeling nanosilicate dust grain growth, revealing how size, composition, and temperature influence their structural and physical properties relevant to astrophysics.

Contribution

NAGGS enables detailed atomistic modeling of nanosilicate grain growth under various conditions, providing new insights into their morphology and dipole moments.

Findings

Surface roughness depends on Mg:Si ratio.

Nanosilicates exhibit high dipole moments influenced by growth temperature.

Growth conditions significantly affect nanograin properties.

Abstract

We report the Nucleated Atomistic Grain Growth Simulator (NAGGS) as a new tool to model the growth of realistic nanosized dust grains through the progressive accretion of monomers onto a nucleated seed. NAGGS can be used with open source molecular dynamics codes, allowing for the modelling of grains that have different chemical compositions and are grown under a range of astrophysical conditions. To demonstrate how NAGGS works, we use it to produce 40 nanosilicate grain models with diameters of approx. 3.5 nm and consisting of approx. 1500 atoms. We consider Mg-rich olivinic and pyroxenic grains, and growth under two circumstellar dust-producing conditions. We calculate properties from the atomistically detailed nanograin structures (e.g. morphology, surface area, density, dipole moments) with respect to the size, chemical composition, and growth temperature of the grains. Our simulations reveal detailed new insights into the complex interacting degrees of freedom during grain growth and how they affect the resultant physicochemical properties. For example, we find that surface roughness depends on the Mg:Si ratio during growth.We also find that nanosilicates have very high dipole moments, which depend on the growth temperature. Such findings could have important consequences (e.g. astrochemistry, microwave emission). In summary, our bottom-up physically motivated approach offers a detailed understanding of nanograins that could help in both interpreting observations and improving dust models.