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

Joan Mariñoso Guiu, Antoni Macià Escatllar, Stefan T. Bromley

TL;DR

The paper introduces NAGGS, a force-field–based simulator for atomistically growing nanoscale dust grains by sequential monomer accretion and directly extracting structure- and property-related metrics. Demonstrated on Mg-rich nanosilicates under circumstellar-like conditions, the method produces amorphous grains up to ~1.5 nm with detailed analyses of composition, radius, sphericity, surface area, silica segregation, density, and electric dipole moments. Key findings show high, size-dependent dipole moments (β>1) with notable composition- and temperature- dependent surface roughness and density trends, and no preferred dipole alignment, all of which have potential implications for anomalous microwave emission and dust modeling. The NAGGS framework offers a versatile platform to study grain growth across compositions and environments, supporting improved interpretation of observations and informing astrophysical dust models.

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.

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 force-field–based simulator for atomistically growing nanoscale dust grains by sequential monomer accretion and directly extracting structure- and property-related metrics. Demonstrated on Mg-rich nanosilicates under circumstellar-like conditions, the method produces amorphous grains up to ~1.5 nm with detailed analyses of composition, radius, sphericity, surface area, silica segregation, density, and electric dipole moments. Key findings show high, size-dependent dipole moments (β>1) with notable composition- and temperature- dependent surface roughness and density trends, and no preferred dipole alignment, all of which have potential implications for anomalous microwave emission and dust modeling. The NAGGS framework offers a versatile platform to study grain growth across compositions and environments, supporting improved interpretation of observations and informing astrophysical dust models.

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.
Paper Structure (19 sections, 8 equations, 20 figures, 3 tables)

This paper contains 19 sections, 8 equations, 20 figures, 3 tables.

Table of Contents

  1. Introduction
  2. The NAGGS code
  3. Nanosilicate grain properties
  4. Chemical composition
  5. Grain radius
  6. Grain sphericity
  7. Grain morphology
  8. Grain surface area
  9. Silica segregation
  10. Grain density
  11. Electric dipole moments
  12. Conclusions
  13. FF parameters used in the MD simulations
  14. Comparison of energetic stabilities of a set of 90 ultrasmall nanosilicate structures as calculated using the employed FF and DFT calculations
  15. Comparison of dipole moments of a set of 90 ultrasmall nanosilicate structures as calculated using the employed FF and DFT calculations
  16. ...and 4 more sections

Figures (20)

  • Figure 1: Upper: Summary of the steps involved in a NAGGS simulation. Lower: Nucleated growth of a nanosilicate grain with respect to the grain radius. Atom colour key: Mg - blue, Si - yellow, O - red.
  • Figure 2: Size-dependent convergence of the Mg:Si ratio for pyroxenic (top) and olivinic (bottom) grain compositions, grown at 600 K and 1100 K. For each chemical composition and temperature, the results of three different NAGGS simulations are shown for each composition-temperature combination. The plots show percentage deviations of the Mg:Si ratio relative to the corresponding stoichiometric values (i.e. zero deviation highlighted by dashed lines). The same analysis for the O:Si ratio can be found in \ref{['o_si_ratio_plot']}.
  • Figure 3: Evolution of nanosilicate grain radius (top) of pyroxene (red) and olivine (blue) grains at 1100K with respect to the number of atoms in the grain. Bottom panel shows the corresponding ratio (as a percentage) of the radii of pyroxene to olivine grains. The results for each grain composition were obtained from averages over ten NAGGS simulations. The corresponding analysis for grains grown at 600K can be found in \ref{['radius_600K']}.
  • Figure 4: Top: Silicate grain sphericity evolution with respect to the number of atoms in the grain for both pyroxene (red) and olivine (blue) composition obtained at 1100K. The bottom panel shows the corresponding ratio (as a percentage) of pyroxene to olivine sphericity. The results were obtained from averages over ten NAGGS simulations. The corresponding analysis for grains grown at 600K can be found in \ref{['sphericity_600K']}.
  • Figure 5: Silicate grain shape evolution for the simulation of pyroxenic composition at 600K pyroxenic composition at 1100K , olivinic composition at 600K and olivinic composition at 1100K (from top to bottom). The black circle indicates the ratio defining a perfect sphere. The grey dashed line corresponds to the cases in which grains would be equally prolate and oblate. The results were obtained as the average over ten NAGGS runs.
  • ...and 15 more figures