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Register a new userRapid Elimination of Small Dust Grains in Molecular Clouds
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We argue that impact velocities between dust grains with sizes less than $sim 0.1$ $mu m$ in molecular cloud cores are dominated by drift arising from ambipolar diffusion. This effect is due to the size dependence of the dust coupling to the magnetic field and the neutral gas. Assuming perfect sticking in collisions up to $approx 50$ m/s, we show that this effect causes rapid depletion of small grains - consistent with starlight extinction and IR/microwave emission measurements, both in the core center ($n sim 10^{6}$ cm$^{-3}$) and envelope ($n sim 10^{4}$ cm$^{-3}$). The upper end of the size distribution does not change significantly if only velocities arising from this effect are considered. We consider the impact of an evolved dust size distribution on the gas temperature, and argue that if the depletion of small dust grains occurs as would be expected from our model, then the cosmic ray ionization rate must be well below $10^{-16}$ s$^{-1}$ at a number density of $10^{5}$ cm$^{-3}$.
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Clustering and dynamics of nano-sized particles (nano dust) is investigated using high-resolution ($1024^3$) simulations of compressible isothermal hydrodynamic turbulence, intended to mimic the conditions inside cold molecular clouds in the interstellar medium. Nano-sized grains may cluster in a turbulent flow (small-scale clustering), which increases the local grain density significantly. Together with the increased interaction rate due to turbulent motions, aggregation of interstellar nano-dust may be plausible.
We present high resolution ($1024^3$) simulations of super-/hyper-sonic isothermal hydrodynamic turbulence inside an interstellar molecular cloud (resolving scales of typically 20 -- 100 AU), including a multi-disperse population of dust grains, i.e., a range of grain sizes is considered. Due to inertia, large grains (typical radius $a gtrsim 1.0,mu$m) will decouple from the gas flow, while small grains ($alesssim 0.1,mu$m) will tend to better trace the motions of the gas. We note that simulations with purely solenoidal forcing show somewhat more pronounced decoupling and less clustering compared to simulations with purely compressive forcing. Overall, small and large grains tend to cluster, while intermediate-size grains show essentially a random isotropic distribution. As a consequence of increased clustering, the grain-grain interaction rate is locally elevated; but since small and large grains are often not spatially correlated, it is unclear what effect this clustering would have on the coagulation rate. Due to spatial separation of dust and gas, a diffuse upper limit to the grain sizes obtained by condensational growth is also expected, since large (decoupled) grains are not necessarily located where the growth species in the molecular gas is.
Density profiles of isolated cores derived from thermal dust continuum emission rely on models of dust properties, such as mass opacity, which are poorly constrained. With complementary measures from near-infrared extinction maps, we can assess the reliability of commonly-used dust models. In this work, we compare Herschel-derived maps of the optical depth with equivalent maps derived from CFHT WIRCAM near-infrared observations for three isolated cores: CB68, L429, and L1552. We assess the dust opacities provided from four models: OH1a, OH5a, Orm1, and Orm4. Although the consistency of the models differs between the three sources, the results suggest that the optical properties of dust in the envelopes of the cores are best described by either silicate and bare graphite grains (e.g., Orm1) or carbonaceous grains with some coagulation and either thin or no ice mantles (e.g., OH5a). None of the models, however, individually produced the most consistent optical depth maps for every source. The results suggest that either the dust in the cores is not well described by any one dust property model, the application of the dust models cannot be extended beyond the very center of the cores, or more complex SED fitting functions are necessary.
We investigate the clustering and dynamics of nano-sized particles (nano-dust) in high-resolution ($1024^3$) simulations of compressible isothermal hydrodynamic turbulence. It is well-established that large grains will decouple from a turbulent gas flow, while small grains will tend to trace the motion of the gas. We demonstrate that nano-sized grains may cluster in a turbulent flow (fractal small-scale clustering), which increases the local grain density by at least a factor of a few. In combination with the fact that nano-dust grains may be abundant in general, and the increased interaction rate due to turbulent motions, aggregation involving nano dust may have a rather high probability. Small-scale clustering will also affect extinction properties. As an example we present an extinction model based on silicates, graphite and metallic iron, assuming strong clustering of grain sizes in the nanometre range, could explain the extreme and rapidly varying ultraviolet extinction in the host of GRB 140506A.
We present a high-sensitivity ($1sigma<1.6~mathrm{mJy~beam^{-1}}$) continuum observation in a 343 arcmin$^2$ area of the northeast region in the Small Magellanic Cloud at a wavelength of 1.1 mm, conducted using the AzTEC instrument on the ASTE telescope. In the observed region, we identified 20 objects by contouring $10sigma$ emission. Through spectral energy distribution (SED) analysis using 1.1 mm, $Herschel$, and $Spitzer$ data, we estimated the gas masses of $5times 10^3-7times 10^4~mathrm{M_odot}$, assuming a gas-to-dust ratio of 1000. Dust temperature and the index of emissivity were also estimated as $18-33$ K and $0.9-1.9$, respectively, which are consistent with previous low resolution studies. The relation between dust temperature and the index of emissivity shows a weak negative linear correlation. We also investigated five CO-detected dust-selected clouds in detail. The total gas masses were comparable to those estimated from the Mopra CO data, indicating that the assumed gas-to-dust ratio of 1000 and the $X_mathrm{CO}$ factor of $1times10^{21}~mathrm{cm^{-2}~(K~km~s^{-1})^{-1}}$, with uncertainties of a factor of 2, are reliable for the estimation of the gas masses of molecular or dust-selected clouds. Dust column density showed good spatial correlation with CO emission, except for an object that associates with bright young stellar objects. The $8~mathrm{mu m}$ filamentary and clumpy structures also showed similar spatial distribution with the CO emission and dust column density, supporting the fact that polycyclic aromatic hydrocarbon emissions arise from the surfaces of dense gas and dust clouds.
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