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Dust Grain Models

95bba3a98c20be969c4fb42ea31ae4ae?s=47 Karl Gordon
October 05, 2020

Dust Grain Models

Literature review and thoughts on dust grain models and modeling for ISM*@ST group.

95bba3a98c20be969c4fb42ea31ae4ae?s=128

Karl Gordon

October 05, 2020
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  1. Dust Grain Models Karl D. Gordon Astronomer STScI, Baltimore, MD

    ISM*@ST Group Meeting 5 Oct 2020 kgordon@stsci.edu @karllark2000 karllark@github
  2. Outline • Bare grain models • Coated grain models •

    Some thoughts • Not an exhaustive review – more illustrative
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  4. Bare Grain Models • Mathis, Rumpl, & Nordseik 1977 •

    Draine & Lee 1984 • Kim et al. 1994, 1995 • Weingartner & Draine 2001 • Clayton et al. 2003 • Zubko, Dwek, & Ardent 2004 • Draine & Li 2007 • Siebenmorgen et al. 2014
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  6. MRN • Has the elements of most grain models since

    1977 • 6 materials – Graphite – Silicon carbide, SiC, Enstatite (Fe,Mg)SiO 3, Olivine (Fe,Mg) 2 SiO 4 – Iron, Magnetite Fe 3 O 4 • Grain shapes: spheres and infinite cylinders • Fit size distribution n(a) as 18 discrete bins from 0 to 1 micron • Constrained by UV/optical extinction and C, Si, Mg, Fe abundances • All fits require C, no strong constraints on the other material (only two components required by data) • Discuss polarization
  7. Mathis, Rumpl, & Nordsieck (1977, ApJ, 217, 425)

  8. Mathis, Rumpl, & Nordsieck (1977, ApJ, 217, 425)

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  10. Kim, Martin, & Hendry • 2 components – graphite and

    silicates – Later work: graphite and modified astronomical silicate • Grain shapes: spheres – Later work: oblate and prolate spheriods w/ a range of axial ratios • Fit mass distributions as 60 discrete bins – Use Maximum Entropy Method • Constrained by extinction, abundances, & (later work) polarization – consistent w/ scattering and IR emission)
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  14. Weingartner & Draine • 2 components • Grain shapes: spheres

    • Fit analytic size distributions • Constrained by extinction & abundances – MW, LMC, and SMC averages
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  19. Zubko, Dwek, & Arendt • 6 possible components – PAHs,

    graphite, 3 types of amorphous carbon – Silicates – Composites of silicates, organics, water ice, and voids • Grain shapes: spheres • Fit size distributions with discrete bins w/ regularization (smoothness) – Provide analytical fits to resulting distributions • Constrained by extinction, abundances, and IR emission • All models investigated fit the constraints used – additional constraints needed
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  23. Coated Grain Models • Greenberg et al. 1966, 1980, 1997

    • Desert et al. 1990 • Jones et al. 2013 (and later)
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  25. Greenberg+ (Li) • 3 components – Large silicate core-organic refractory

    mantle – Very small carbonaceous particles – PAHs • Grain shapes: spheres and finite cylinders • Fit exponential size distributions • Constrained by UV-MIR extinction, polarization, and C, Si, Mg, Fe, O, & N abundances
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  29. Desert, Boulanger, & Puget • 3 components – Big silicate

    grains coated with carbonaceous material – PAH (molecules) – Very small grains of amorphous carbon • Grain shapes • Fit to powerlaw size distributions • Constrained by extinction & emission • Introduces “astronomical PAHs”
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  33. Jones, et al. • 3 components (families of grains –

    dust evolution model) – Amorphous carbon with size dependent properties – Amorphous silicates with amorphous carbon mantles – Coagulated carbonaceous/silicate grains • Grain shapes: spheres • Fit analytic size distributions (chi-by-eye?) • Constrained by extinction, abundances, emission, and albedo – Also explains trends seen in extinction characteristics
  34. Coated Grains Model Jones et al. (2013)

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  36. Chiar et al. (2013, ApJ, 770, 78)

  37. Some Thoughts

  38. Geography Matters • Mostly Americans → Bare grains – Influence

    of Mathis? • Mostly Europeans → Coated grains – Influence of Greenberg?
  39. Astrodust? • Draine & Hensley (2020, ApJ, submitted) • 3

    components – Astrodust: composite of silicates, hydrocarbons, + – Nanoparticles of PAHs and silicates
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  41. Ideal grain model • Fit MW/SMC/LMC(/other LG) – averages and

    variations • Uses all available data – Extinction, abundances, thermal and non-thermal emissions, scattering, polarization
  42. DGFit Motivation • Calculate how new observations affect our understanding

    of dust grains – Bigger/smaller grains, new materials, ... • Quantitatively compare different grain materials – Bayesian statistics may help (Bayes Factors) • Add additional observational constraints – E.g., albedo and scattering phase function asymmetry
  43. MW Diffuse Dataset

  44. DGFit Gordon & Misselt (202x, in prep)

  45. Updated Obs & Albedo

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  49. Backup

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  51. Draine & Lee • Mainly introducing “astronomical silicate” and “astronomical

    graphite” based on heterogeneous lab data • 2 components • Grain shapes: spheres • Test MRN powerlaw size distributions • Constrained by extinction & emission
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  56. Clayton et al. • 3 components – Graphite, amorphous carbon

    – Silicates • Grain shapes: spheres • Fit mass distributions as 60 discrete bins (MEM) • Constrained by extinction & abundances • Fit MW, LMC, SMC and individual sightlines
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  60. Draine & Li • Update “astronomical PAHs” to match Spitzer

    Obs • 2 components – Silicates – Carbonaceous (PAH/graphite) • Grain shapes: spheres • Fit analytic size distributions – Tweaks to Weingartner & Draine results • Constrained by extinction, abundances, & emission
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  63. Siebenmorgen et al. • 2 components – Amorphous carbon –

    Amorphous silicates • Grain shapes: spheroids • Fit mass distributions as 60 discrete bins (MEM) • Constrained by extinction, abundances, emission, & polarization • Fit individual sightlines
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