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Chemistry on dust grains
Interstellar dust grains find their origin in the material ejected from stars. They form in dense environment such as the atmosphere of evolved stars, from which they are released in the ISM via radiation pressure, stellar winds, or novae and supernovae ex-plosions. The size of the grains can go from a few nanometers to several micrometers for the biggest ones, and they are composed of either silicates or amorphous carbon (Lequeux, 2005; Draine, 2011).
Before the advent of IR spectroscopy, interstellar grains were merely an annoyance for astronomers because of the phenomenon called interstellar extinction, namely that they efficiently absorb light within wavelengths from UltraViolet (UV) to the visible. However, thanks to IR observations, the interstellar grains population appeared to be a significant compound of astrophysical processes despite the fact that it represents only 1% of the ISM mass. Indeed, the light absorbed by the grains is reemitted at IR and sub-millimeter wavelength via the process called interstellar reddening, allowing astrophysicists to study the grains’ role and properties in the ISM. The interstellar red-dening phenomenon is illustrated in figure 1.3.
Thermal processes
Interstellar grains participate actively in the heating of the gas, especially in regions prone to intense UV radiations. In fact, the incident UV photons tear electrons off the grains surface via photoelectric effects. The freed electrons then furnish energy to the surrounding gas via thermalization.
Surface chemistry
The grains also participate actively to the ISM chemistry, notably as a catalyst for chemical reactions. As such, they allow the efficient formation of H2, the most abun-dant molecule of the universe (Lequeux, 2005; Draine, 2011). Surface reactions happen via the following process:
1. The adsorption of gas phase species onto the grains surface via physisorption, ie via van der Walls interactions, which depends mainly on the collision rate be-tween molecules and grains, and therefore the density of the medium.
2. The diffusion of the species on the grains surface, which depends mainly on the grains temperature, the nature of its core, as well as its porosity.
3. The reaction of the species upon encounter with another one.
The product species can then either keep on diffusing on the surface, or desorb back into the gas phase.
A word about laboratory experiments
As seen in section 1.1.1, laboratory experiments play a significant role in the spec-troscopy aspect of astrochemistry, namely by measuring the emission spectra of inter-stellar species. Another paramount role of laboratory experiment is to measure and calculate the parameters needed to correctly model chemical reactions. Equation (1.3) shows for example the importance of a good determination of the rate constant k, which mainly depends on parameters of the reactions that can only be measured in laboratory, such as its activation energy.
The NAUTILUS chemical model
The NAUTILUS chemical model computes the evolution of chemical abundances by solving a system of differential equations similar to (1.5). The model uses the « rate equation » approach, which consists in considering that the system evolution is con-tinuous and deterministic, ie the state of the system at any given time can be inferred from its initial state. It can simulate a 3-phases chemistry including gas phase, grains surface and grains bulk chemistry, along with the possible exchanges between the dif-ferent phases (Ruaud et al., 2016). The processes taken into account in the model are described in the following.
Current hypothesis on the reservoirs of sulphur in dark clouds
The main hypothesis to explain the missing sulphur in dark clouds is that it is de-pleted onto interstellar grains. In cometary ices, which are thought to present chem-ical similarities with the ices formed in dark clouds (Irvine et al., 2000), H2S is the most abundant S-bearing molecule, at the level of 1.5% compared to water (Bockelée-Morvan et al., 2000). More recently, Holdship et al. (2016) derived the abundance and deuteration fraction of H2S in the low-mass protostar L1157-B1. By comparing the observations to chemical models with different branching ratios for the freeze out of S-bearing species into OCS and H2S, they found that a significant fraction of the sul-phur is likely to be locked into the form of H2S on the grains. Chemical models also predict that, in the dense interstellar medium, atomic sulphur would stick on grains and be mostly hydrogenated to form H2S. To this day however only OCS (Palumbo et al., 1997) and SO2 (Boogert et al., 1997) have been likely identified in icy grains bulk in dense molecular clouds surrounding high-mass protostars, and their estimated total abundance does not account for the missing sulphur. Upper limits of at most 3 1016 cm 2 for the column density of H2S in icy grains bulk have been derived by Smith (1991), notably towards the line of sight of three late-type field stars lying behind the Taurus molecular cloud, but they are also too low for H2S to be the reservoir of sulphur in dark clouds.
Laboratory experiments coupled with chemical models have recently brought new insight into the problem by studying the irradiation of H2S interstellar ice analogs by energetic protons and UV photons by Garozzo et al. (2010) and Jiménez-Escobar and Muñoz Caro (2011). Both studies found that solid H2S was easily destroyed to form other species such as OCS, SO2, CS2 and H2S2. In the study presented hereafter, I propose an enhancement of the sulphur chem-ical network for dark clouds models motivated by the recent observations of HNCS and HSCN in TMC-1 (CP) (Adande et al., 2010) and of CH3SH in IRAS 16293-2422 (Majumdar et al., 2016). My network also includes the network proposed by Druard and Wakelam (2012). I test the effect of the updated network on the outputs of the NAUTILUS chemical model for dark cloud conditions using different sulphur elemen-tal abundances. More particularly, I focus my study on the main sulphur reservoirs as well as on the agreement between model predictions and the abundances observed in the dark cloud TMC-1 (CP). The state of the NAUTILUS chemical model used is the same as presented in section 1.1.3. In the following, I first detail the modifications of the chemical network and describe the new modeling results, including a comparison with the previous version of the network. Then I compare these results with obser-vations towards the dark cloud TMC-1 (CP), to finally discuss and conclude on the results.
Effects of the new network on the chemical model of dark clouds
In this section I highlight the impact of the enhanced sulphur network on the outputs of the Nautilus chemical model configured for dark clouds physical conditions. I first present the abundance evolution of the most abundant sulphur-bearing species as well as the newly implemented ones. Then I compare the outputs obtained with the new network with those obtained with the nominal network for the same model configura-tion.
The newly implemented sulphur bearing species
Among the 45 new S-bearing species included in the network, I present below the re-sults of the model for HNCS, the species around which most of the new network has been built, and CH3SH, which was recently detected in the envelope of the low-mass protostar IRAS 16293-2422 (Majumdar et al., 2016).
Table of contents :
1 INTRODUCTION
1.1 REVISITING THE CHEMISTRY
1.1.1 Spectroscopy’s principle
1.1.2 Chemical modeling and laboratory experiments
1.1.2.1 Chemistry in the interstellar gas
1.1.2.2 Chemistry on dust grains
1.1.2.3 Generalities on chemical modeling
1.1.2.4 A word about laboratory experiments
1.1.3 The NAUTILUS chemical model
1.1.3.1 Gas phase chemistry
1.1.3.2 Grains chemistry
1.2 … OF STAR FORMATION
1.2.1 From diffuse clouds to dense clouds
1.2.2 Cloud collapse and star formation
1.2.3 The death of stars
1.3 OBJECTIVES AND ORGANIZATION OF THE THESIS
2 SULPHUR CHEMISTRY IN DARK CLOUDS
2.1 INTRODUCTION
2.1.1 The sulphur depletion problem
2.1.2 Current hypothesis on the reservoirs of sulphur in dark clouds .
2.2 PRESENTATION OF THE ENHANCED CHEMICAL NETWORK
2.2.1 Modification of the sulphur network
2.2.2 Effects of the new network on the chemical model of dark clouds
2.2.2.1 The main sulphur bearing species
2.2.2.2 The newly implemented sulphur bearing species
2.2.2.3 Comparison with the previous network
2.3 COMPARISON WITH OBSERVATIONS IN THE DARK CLOUD TMC-1 .
2.3.1 Comparison with models A and B
2.3.2 Variation of the elemental sulphur abundance
2.3.2.1 Comparison with all observed gas phase species
2.3.2.2 Comparison with observed sulphur bearing gas phase species
2.3.2.3 The new species HNCS and HSCN
2.3.2.4 Sulphur bearing species on grains towards W33A
2.3.3 Sulphur reservoirs in dark clouds
2.4 DISCUSSIONS AND SUMMARY
2.4.1 About the elemental abundance of sulphur
2.4.2 About the reservoirs of sulphur in dark clouds
2.4.3 About the observability of HCS
2.4.4 Summary
3 A NEW LOOK AT SULPHUR CHEMISTRY IN HOT CORES AND CORINOS
3.1 INTRODUCTION
3.2 MODELS PARAMETERS
3.2.1 H2 ad hoc formation mechanism
3.2.2 Parent dark cloud parameters
3.2.3 Hot core models parameters
3.2.3.1 The 0D static model parameters
3.2.3.2 The 1D static model parameters
3.2.3.3 The 0D dynamic model parameters
3.3 HOT CORE CHEMISTRY
3.3.1 0D models
3.3.1.1 Oxygen chemistry
3.3.1.2 Sulphur chemistry
3.3.1.3 Comparisons to observations
3.3.2 1D static models
3.3.3 0D dynamic models
3.4 DISCUSSIONS AND SUMMARY
3.4.1 About the modification of the density profile of the dynamic model
3.4.2 About H2S and the initial abundance of sulphur
3.4.3 About the sensitivity to the type of model
3.4.4 About the importance of the pre-collapse chemical composition .
3.4.5 Summary
4 CONSTRAINING THE IPPC OF COLLAPSING PRESTELLAR CORES
4.1 INTRODUCTION
4.2 RHD CHEMICAL COLLAPSE MODELS OF LOW-MASS STAR FORMATION
4.2.1 The database
4.2.1.1 Bonnor-Ebert spheres
4.2.1.2 The Lagrangian grid
4.2.1.3 Initial setup of the collapse models
4.2.2 Chemical modeling
4.2.2.1 Selection of the reference dataset for chemical modeling
4.2.2.2 Parameters of the chemical modeling
4.3 POST-TREATMENT OF THE CHEMICAL OUTPUTS AND RESULTS
4.3.1 Search for tracers of initial physical parameters of collapse
4.3.1.1 Definition of the regions of study
4.3.1.2 Correlations in the Hot Corinos Region
4.3.2 Constraints on the envelope of Class 0 protostars
4.3.2.1 Presentation of the method
4.3.2.2 Results on the envelope of IRAS 16293-2422
4.3.2.3 Summary of the results on the source sample
4.4 DISCUSSIONS AND SUMMARY
4.4.1 About the modeling bias
4.4.2 About the applicability of the method on the HCR dataset
4.4.3 Summary
5 CONCLUSIONS AND PERSPECTIVES
A SUMMARY OF SULPHUR COMPOUNDS REACTIONS REVIEW
B INITIAL PARAMETERS OF THE RADIATION HYDRODYNAMIC MODELS
C CORRELATIONS IN THE HOT CORE REGION
D CONSTRAINTS ON THE IPPC FOR EACH SOURCES
E ACRONYMS AND SYMBOLS
F INTRODUCTION
F.1 REVISITER LA CHIMIE
F.1.1 Généralités
F.1.2 Le modèle de chimie NAUTILUS
F.1.2.1 Chimie en phase gazeuse
F.1.2.2 Chimie sur les grains
F.2 …DE LA FORMATION STELLAIRE
F.2.1 Des nuages diffus aux nuages denses
F.2.2 Effondrement et formation stellaire
F.3 OBJECTIFS ET ORGANISATION DE LA THÈSE
G RÉSUMÉ, CONCLUSIONS ET PERSPECTIVES
H PUBLICATIONS
BIBLIOGRAPHIE
