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In this work we investigate the effects of ion accretion and size-dependent dust temperatures on the abundances of both gas-phase and grain-surface species. While past work has assumed a constant areal density for icy species, we show that this assumption is invalid and the chemical differentiation over grain sizes are significant. We use a gas-grain chemical code to numerically demonstrate this in two typical interstellar conditions: dark cloud (DC) and cold neutral medium (CNM). It is shown that, although the grain size distribution variation (but with the total grain surface area unchanged) has little effect on the gas-phase abundances, it can alter the abundances of some surface species by factors up to $sim2-4$ orders of magnitude. The areal densities of ice species are larger on smaller grains in the DC model as the consequence of ion accretion. However, the surface areal density evolution tracks are more complex in the CNM model due to the combined effects of ion accretion and dust temperature variation. The surface areal density differences between the smallest ($sim 0.01mu$m) and the biggest ($sim 0.2mu$m) grains can reach $sim$1 and $sim$5 orders of magnitude in the DC and CNM models, respectively.
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Interstellar polarization in the optical/infrared has long been known to be due to asymmetrical dust grains aligned with the magnetic field and can potentially provide a resource effective way to probe both the topology and strength of the magnetic field. However, to do so with confidence, the physics and variability of the alignment mechanisms must be quantitatively understood. The last 15 years has seen major advancements in both the theoretical and observational understanding of this problem. I here review the current state of the observational constraints on the grain alignment physics. While none of the three classes of proposed grain alignment theories: mechanical, paramagnetic relaxation and radiative alignment torque, can be viewed as having been empirically confirmed, the first two have failed some critical observational tests, whereas the latter has recently been given specific observational support and must now be viewed as the leading candidate.
We used the new IRAM 30-m FTS backend to perform an unbiased ~15 GHz wide survey at 3 mm toward the Pipe Nebula young diffuse starless cores. We found an unexpectedly rich chemistry. We propose a new observational classification based on the 3 mm molecular line emission normalized by the core visual extinction (Av). Based on this classification, we report a clear differentiation in terms of chemical composition and of line emission properties, which served to define three molecular core groups. The diffuse cores, Av<~15, show poor chemistry with mainly simple species (e.g. CS and CCH). The oxo-sulfurated cores, Av~15--22, appear to be abundant in species like SO and SO2, but also in HCO, which seem to disappear at higher densities. Finally, the deuterated cores, Av>~22, show typical evolved chemistry prior to the onset of the star formation process, with nitrogenated and deuterated species, as well as carbon chain molecules. Based on these categories, one of the diffuse cores (Core 47) has the spectral line properties of the oxo-sulfurated ones, which suggests that it is a possible failed core.
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We have carried out mapping observations of molecular emission lines of HC$_{3}$N and CH$_{3}$OH toward two massive cluster-forming clumps, NGC2264-C and NGC2264-D, using the Nobeyama 45-m radio telescope. We derive an $I$(HC$_{3}$N)/$I$(CH$_{3}$OH) integrated intensity ratio map, showing a higher value at clumps including 2MASS point sources at the northern part of NGC2264-D. Possible interpretations of the $I$(HC$_{3}$N)/$I$(CH$_{3}$OH) ratio are discussed. We have also observed molecular emission lines from CCS and N$_{2}$H$^{+}$ toward five positions in each clump. We investigate the $N$(N$_{2}$H$^{+}$)/$N$(CCS) and $N$(N$_{2}$H$^{+}$)/$N$(HC$_{3}$N) column density ratios among the ten positions in order to test whether they can be used as chemical evolutionary indicators in these clumps. The $N$(N$_{2}$H$^{+}$)/$N$(CCS) ratio shows a very high value toward a bright embedded IR source (IRS1), whereas the $N$(N$_{2}$H$^{+}$)/$N$(HC$_{3}$N) ratio at IRS1 is comparable with those at the other positions. These results suggest that UV radiation affects the chemistry around IRS1. We find that there are positive correlations between these column density ratios and the excitation temperatures of N$_{2}$H$^{+}$, which implies the chemical evolution of clumps. These chemical evolutionary indicators likely reflect the combination of evolution along the filamentary structure and evolution of each clump.
The characterization of interstellar chemical inventories provides valuable insight into the chemical and physical processes in astrophysical sources. The discovery of new interstellar molecules becomes increasingly difficult as the number of viable species grows combinatorially, even when considering only the most thermodynamically stable. In this work, we present a novel approach for understanding and modeling interstellar chemical inventories by combining methodologies from cheminformatics and machine learning. Using multidimensional vector representations of molecules obtained through unsupervised machine learning, we show that identification of candidates for astrochemical study can be achieved through quantitative measures of chemical similarity in this vector space, highlighting molecules that are most similar to those already known in the interstellar medium. Furthermore, we show that simple, supervised learning regressors are capable of reproducing the abundances of entire chemical inventories, and predict the abundance of not yet seen molecules. As a proof-of-concept, we have developed and applied this discovery pipeline to the chemical inventory of a well-known dark molecular cloud, the Taurus Molecular Cloud 1 (TMC-1); one of the most chemically rich regions of space known to date. In this paper, we discuss the implications and new insights machine learning explorations of chemical space can provide in astrochemistry.
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