A three-phase chemical model of hot cores: the formation of glycine
aa r X i v : . [ a s t r o - ph . GA ] F e b A three-phase chemical model of hot cores:the formation of glycine
Robin T. Garrod
Center for Radiophysics and Space Research, Cornell University, Ithaca, NY 14853-6801, USA [email protected]
ABSTRACT
A new chemical model is presented that simulates fully-coupled gas-phase, grain-surface and bulk-ice chemistry in hot cores. Glycine (NH CH COOH), the simplestamino acid, and related molecules such as glycinal, propionic acid and propanal, areincluded in the chemical network. Glycine is found to form in moderate abundancewithin and upon dust-grain ices via three radical-addition mechanisms, with no singlemechanism strongly dominant. Glycine production in the ice occurs over temperatures ∼ × - –8 × - , occuring at ∼
200 K, the evaporation temperature of glycine. A gas-phasemechanism for glycine production is tested and found insignificant, even under op-timal conditions. A new spectroscopic radiative-transfer model is used, allowing thetranslation and comparison of the chemical-model results with observations of specificsources. Comparison with the nearby hot-core source NGC 6334 IRS1 shows excellentagreement with integrated line intensities of observed species, including methyl for-mate. The results for glycine are consistent with the current lack of a detection of thismolecule toward other sources; the high evaporation temperature of glycine rendersthe emission region extremely compact. Glycine detection with ALMA is predictedto be highly plausible, for bright, nearby sources with narrow emission lines. Pho-todissociation of water and subsequent hydrogen-abstraction from organic moleculesby OH, and NH , are crucial to the build-up of complex organic species in the ice.The inclusion of alternative branches within the network of radical-addition reactionsappears important to the abundances of hot-core molecules; less favorable branchingratios may remedy the anomalously high abundance of glycolaldehyde predicted bythis and previous models. Subject headings:
Astrochemistry, Astrobiology, ISM: molecules, molecular processes,ISM: lines and bands, Radiative transfer 2 –
1. Introduction
Millimeter, sub-millimeter, and centimeter wavelength observations of star-forming sourcesknown as “hot cores” reveal a range of complex organic molecules, through the identification ofmolecular rotational emission spectra (Herbst & van Dishoeck 2009). Many of the moleculesdetected toward hot cores are highly saturated (i.e. hydrogen-rich), and a significant number alsocontain oxygen and/or nitrogen; examples include methanol (CH OH), formic acid (HCOOH),and the ubiquitous methyl formate (HCOOCH ), as well as the recently detected aminoacetonitrile(NH CH CN, Belloche et al. 2008), which bears both amine and nitrile groups. The breadth offunctional groups borne by molecules detected toward hot cores (as well as the large number ofunidentified emission lines) suggests that other, as-yet undetected species may also be present,including biologically-significant molecules such as amino acids – the building blocks of proteins.The search for the simplest amino acid, glycine (NH CH COOH), toward interstellar sourceshas not so far yielded a detection (Snyder et al. 2005); recent upper limits toward Sgr B2(N),a spectrally- and chemically-rich hot-core source in the Galactic Center, are around 10 – 10 cm - for beam-averaged values obtained with the Mopra telescope (Cunningham et al. 2007) andthe ATCA array (Jones et al. 2007) for glycine conformer I. Upper limits on the higher-energyconformer II from the same studies are around 10 – 10 cm - . However, numerous amino acidshave been found in meteorites, and glycine was recently detected in a sample taken from cometWild 2 (Elsila et al. 2009); it has indeed been postulated that terrestrial amino acids may have aninterstellar origin (e.g. Ehrenfreund & Charnley 2000).It is likely that amino acids and other biologically-relevant species will, in the coming years,provide plausible targets for searches with the ALMA telescope, which can provide much greatersensitivity and spatial resolution than was previously available. It is therefore valuable to extendexisting astrochemical models to simulate the putative formation of glycine and related speciesin hot cores, both to make quantitiative predictions and to assess the viability of observationalcandidate sources.Current models of hot-core chemistry place great emphasis on the formation of organic moleculeswithin or upon dust-grain ice mantles, as well as in the gas phase. Garrod & Herbst (2006, hereafterG&H) showed that typically-observed molecules such as methyl formate, while difficult to formby gas-phase mechanisms, could be produced in appropriate abundances through grain-surfacechemistry at intermediate temperatures, prior to the complete sublimation of the dust-grain ices.The radicals HCO and CH were found to become mobile around 20 – 40 K, reacting with otherradicals associated with formaldehyde and methanol destruction, to produce formic acid, dimethylether and methyl formate. Cosmic ray-induced photolysis of the molecular ice mantles was foundto be the dominant source of these functional-group radicals. Garrod, Widicus Weaver & Herbst(2008, hereafter GWH) extended the network to include a much larger number of surface radi- 3 –cal species, allowing the study of more complex molecules; methanol was found to be the keymolecule for the supply of the constituent functional groups of many such species.Recent experimental work by Öberg et al. (2009a) has provided direct evidence that a range ofcomplex organic molecules detected in star-forming regions may be readily produced within UV-irradiated organic ices. Other studies focused specifically on amino-acid formation have elucidateda number of potential chemical pathways for glycine within laboratory ice mixtures. Experimentsby Bernstein et al. (2002) and Muñoz Caro et al. (2002) showed that UV irradiation of interstellarice analogs containing H O, CH OH, CO, CO , NH and/or HCN could produce significant quan-tities of amino acids, including glycine. Sorrell (2001) had suggested a route involving the reactionof the NH radical with acetic acid (CH COOH), itself formed through the addition of CH andHOCO, while Woon (2002) suggested that the addition reaction between radicals NH CH andHOCO could explain the formation of glycine, with these species produced in the ices by succes-sive hydrogenation of HCN and by the addition of CO and OH, respectively. Experimental workby Holtom et al. (2005) involving the electron bombardment of CO /NH CH ices confirmed theviability of Woon’s mechanism, while work by Elsila et al. (2007), extending the investigationof Bernstein et al. (2002), used isotopic labeling to trace the origins of the constituent atoms inthe product molecules. Their findings indicated that Woon’s mechanism was consistent with theorigins of the nitrogen and central carbon in the glycine molecule, while the origin of the acidiccarbon was more consistent with the formation of glycine occurring via a nitrile precursor, i.e.amino acetonitrile (NH CH CN). However, a Strecker-type formation route was found to be ofonly minor importance.In order to investigate the formation of glycine within dust-grain ices under astrophysical con-ditions, the extension of the chemical networks of G&H and GWH – as well as that of Belloche etal. (2009), who treated the formation of amino acetonitrile, n -propyl cyanide, and ethyl formate –is continued with the addition of glycine, its amino aldehyde glycinal, and a collection of relatedspecies such as propionic acid and propanal. The new formation mechanisms for these species fol-low the general treatments of previous networks, which allowed radicals on the grains, frequentlyproduced by UV photodissociation or chemical abstraction processes, to meet via thermal diffusionand thus form more complex structures. The mechanism suggested by Woon (2002) is includedin the new network, as well as several other likely radical-addition mechanisms. Furthermore, agas-phase mechanism for glycine production is tested, by the inclusion of reactions between proto-nated hydroxylamine (NH OH + ) and acetic acid (CH COOH), followed by dissociative electronicrecombination, as suggested by Blagojevic et al. (2003). All new species in the network are af-forded both formation and destruction mechanisms on the grains and in the gas-phase. A morecomprehensive hydrogen-abstraction reaction set is also included in the network.To apply this chemical network to hot-core conditions, a new three-phase astrochemical 4 –model,
MAGICKAL , is used, which includes a fully-active chemistry within the bulk of the icemantle (see Section 2.1). The physico-chemical evolution of the core is traced starting from thefree-fall collapse of a cloud, using the dust-temperature/visual-extinction relationship given byG&P, through the subsequent warm-up of the dense core from 8 – 400 K.In order to simulate the emission from glycine and a selection of other molecules, the re-sults of these models are mapped to existing observationally-determined temperature and densityprofiles for specific sources. The equation of radiative transfer is then solved numerically, underthe assumption of local thermodynamic equilibrium, along both on- and off-source lines of sight,allowing a determination of line strengths and emission radii. This emission is then convolvedwith telescope beams appropriate to current instruments, allowing the detectability of glycine tobe assessed. The nearby hot-core source NGC 6334 IRS1 is specifically considered, due both tothe availability of physical profiles and molecular observations in the literature, and to its spec-troscopic suitability. Comparison is also made with the recent non-detection of hydroxylamine(NH OH) in another source (Pulliam et al. 2012), with implications for the putative formation ofglycine in the gas phase.Section 2 describes the new chemical and physical models; the results are presented in Section3. The results of the inclusion of gas-phase formation mechanisms for glycine are described inSection 4. The spectroscopic model and results for various molecules are presented in Section 5.A broad discussion of the results is presented in Section 6; a list of general conclusions is providedin Section 7.
2. Chemical modeling
To model the hot-core chemistry, a new astrochemical code is employed, named
MAGICKAL (Model for Astrophysical Gas and Ice Chemical Kinetics And Layering). This code uses a rate-equation/modified rate-equation approach to solve the coupled gas-phase, dust grain-surface andice-mantle chemistry. The essential functionality of previous approaches (Garrod & Pauly, 2011)is retained, while a number of additional features are added, as outlined below.
The three-phase model used here is described in detail by Garrod & Pauly (2011), and is basedon the approach of Hasegawa & Herbst (1993). In contrast to both of those methods,
MAGICKAL simulates an active ice-mantle chemistry in addition to that occurring in the surface layer of theice or on the dust-grain surface. Previous two-phase hot-core models, such as those of G&H, 5 –GWH, and Belloche et al. (2009), have implicitly assumed a combined surface/mantle chemistry,using surface kinetics to simulate all dust-grain chemical processes, including those within the bulkice. Although satisfactory results may be obtained through this simplification, it has become clearthrough experimental means (e.g. Öberg et al., 2009a) that the promotion of complex-moleculeformation within organic ices by UV photolysis involves sub-surface processes, even in relativelythin ices (on the order of 10 monolayers).In order to simulate chemical kinetics within the ice mantles, it is here assumed that the mo-bility of chemical reactants in the bulk ice occurs through a barrier-mediated thermal diffusionprocess. Other authors have assumed a swapping mechanism to be active in laboratory ice experi-ments (Öberg et al. 2009; Fayolle et al. 2011), which is also implicitly assumed in this model. Theswapping rate is parameterized in the same way as the surface thermal hopping, i.e. k swap ( i ) = ν ( i ) exp[ - E swap ( i ) / T d ] (1)where ν is the characteristic vibrational frequency of an harmonic oscillator, T d is the dust tem-perature, and E swap is an energy barrier associated with the swapping of species i with an adjacentwater molecule, in line with the adoption of surface binding energies appropriate to amorphouswater ice, following G&H and GWH.Ratios between the surface diffusion barrier and the desorption energy of any particularspecies bound to an ice or any other surface are poorly constrained, and various authors haveused values in the approximate range of 0.3 – 0.8. Garrod & Pauly (2011) found that the produc-tion of interstellar CO ice could be well reproduced by the adoption of ratios E dif : E des . .
4; herea value of 0.35 is used. Thence, a value of E swap : E des = 0 . R AB = N m ( A ) N m ( B ) [ k swap ( A ) + k swap ( B )] / N M (2)where N m ( i ) is the population of species i in the ice mantle, and N M is the total population of theice mantle, including all species.As discussed by Garrod & Pauly (2011), in the three-phase model, material in the surfacelayer is transferred to the bulk ice according to the net rate of deposition of material onto the grainfrom the gas phase, with a similar, alternative transfer occurring in reverse in the case of a net 6 – desorption of mantle species into the gas phase. These transfers represent the covering or exposureof ice material as the boundary of the ice-surface layer is constantly re-defined within the model,rather than the physical transport of material. However, the inclusion of bulk diffusion within theice should allow a true exchange of chemical species between surface and mantle, through theaforementioned swapping mechanism.This surface–mantle swapping is a pair-wise process, and therefore requires the constructionof rates for each chemical species in the mantle and in the surface layer, which must collectivelyproduce no net transfer between the two phases. This zero net rate would be assured using anexplicit pair-wise coupling of every species in the surface with every species in the grain mantle;however, such an approach is found to be computationally exhaustive, and requires estimates ofthe pair-wise positions of the swapped species that a rate-based model cannot provide, other thanthrough purely statistical considerations.Instead, the swapping rates from mantle to surface are calculated first, with rates analogous tothat of equation (2). The total rate in this direction is then matched with an identical total transferrate from surface to mantle, apportioned to all the surface species according to their fractionalcontribution to the total surface-layer population. Thus: R swap , m ( i ) = N m ( i ) N S N M k swap ( i ) (3) R swap , s ( i ) = N s ( i ) N S · X all j R swap , m ( j ) (4)where R swap , m ( i ) is the rate of mantle-to-surface swapping of mantle species i , R swap , s ( i ) is therate of surface-to-mantle swapping of surface species i , N m ( i ) and N s ( i ) are the mantle and surfacepopulations, respectively, of species i , and N M and N S are the total mantle and surface populations.The ratio N S / N M in equation (3) is taken as unity when it exceeds this value, representing the casewhere some surface species reside on the dust-grain surface itself and have no underlying mantle.Because the model does not assign specific positions to each atom or molecule in the mantle,the rate of mantle-to-surface swapping, R swap , m ( i ), is required to be representative not simply of thefinal diffusion step, but of the entire chain of diffusion steps by which a mantle species at arbitrarydistance from the surface layer will reach the surface. The use of k swap in eq. (3) as the rate of atypical, or average, step in this process is accurate so long as the final diffusion step from mantleto surface is relatively fast, i.e. that intra-mantle diffusion is the rate-limiting step in the entirejourney from mantle to surface. Under the assumption that the ice is predominantly water ice (see 7 –above), the final surface-to-mantle step will be fast for species whose binding energies are lessthan or similar to that of water. For the small minority of species with significantly greater bindingenergies than this, for which there would thus be an associated endothermicity to the mantle–surface swap with a water molecule (see e.g. Öberg et al. 2009b), the large absolute size of theswapping barrier would render the rate of mantle-to-surface diffusion negligible compared to otherprocesses, such as the mantle-to-surface transfer associated with net surface desorption.These rates defined in eqs. (3) and (4) are also considered in the loss and gain rates used forthe modified-rate calculations of Garrod (2008), which are applied in this model (using "methodC"). Garrod et al. (2009) showed that this method produces a very close approximation to theresults of exact Monte Carlo methods, using a large chemical network under a range of physicalconditions. The chemical network used in this model is based on that of GWH and the subsequent addi-tions of Belloche et al. (2009), which featured a treatment for nitriles, including amino acetonitrile(NH CH CN). These networks assumed grain-surface radical–radical formation mechanisms fornewly-added complex organic molecules, as well as destruction mechanisms such as grain-surfaceand gas-phase photodissociation (by both the ambient and cosmic ray-induced UV fields), gas-phase ion-molecule reactions (including protonation) and the related electronic recombinations ofthe products, as well as accretion from the gas-phase onto the grain surfaces, and thermal andnon-thermal desorption from the grains. The initial elemental abundances used are shown in Table1. Laas et al. (2011) constructed a network of reactions to treat the formation of trans -methyl for-mate, the higher energy conformer of the commonly observed cis -methyl formate; however, thatstudy found no significant effect on the abundances of species other than trans -MF, so the omissionof the related chemistry is not expected to have any effect on the models presented here.Following the same methodology, formation and destruction processes are included for glycineand a suite of related molecules, including glycinal, propanal and propionic acid. Radical–radicalreactions for a selection of these species are shown in Table 2. Whereas in the previous models,a single complex molecule was typically assumed to be the only possible product of the additionof key grain-surface radicals, here alternative product branches are included, for the case wheresuch a reaction could also result in a pair of stable products, and where the reaction is also exother-mic. Thus, for the reaction HCO + CH O → HCOOCH , which was found by GWH to be thepredominant formation route for methyl formate, alternative product branches of [CO + CH OH]and [H CO + H CO] are now also included. The branching ratios are in general poorly defined, 8 –and are likely to be significantly different between the gas- and solid-phase processes; statisticalratios are therefore adopted (e.g. 1:1:1 for HCO + CH O). In addition, the same such two-productreactions are now also included in the gas-phase chemistry, using measured rates where available;otherwise, a uniform second-order rate coefficient of 10 - cm s - is assumed. Such processesmay become important in the late, high-temperature stage of hot-core evolution, during which theevaporation, protonation and subsequent electronic recombination may lead to significant quanti-ties of molecular radicals being present in the gas phase. However, the single-product branchesare omitted from the gas-phase chemistry, because of their negligible rates, due to the absence of agrain surface to carry away excess energy and thereby stabilize the product.Following previous models, grain-surface hydrogen-abstraction reactions are added for reac-tions between the new complex species and the most significant grain-surface radicals such as H,OH, CH , CH OH, CH O and NH . Table 3 shows activation-energy barrier information used inthe model, for a selection of (primarily hydrogen-abstraction) reactions occurring on the grains.For atomic-hydrogen reactions relating to methanol formation, for which more complex fits totheoretical rates are employed, the simpler rectangular-barrier parameter fits are quoted, as for allother barrier-mediated reactions. The method of Hasegawa et al. (1992) is used to calculate thetunneling and thermal rates associated with these parameters, adopting the faster of the two for anygiven temperature. For the majority of reactions, only gas-phase data are available, in which casethe activation energy derived from fits to the lowest-temperature data-sets available are adoptedfor the surface/mantle reactions, assuming a barrier width of 1 Å. In cases where no data exist,the activation energy, E A , is estimated using the Evans-Polanyi relationship, which states that thedifference in E A between reactions of a similar type is proportional to the difference between theenthalpy changes associated with each reaction. Parameters for the Evans-Polanyi relationship areobtained from Dean & Bozzelli (1999), or from fits using similar reactions, indicated in Table3. Where the enthalpy change of reaction is unknown, the activation energy of a similar reac-tion is used directly. There is evidence that the presence of a surrounding water-ice matrix mayalter activation energy barriers for specific product branches (e.g. Goumans 2011, in the case offormaldehyde-related chemistry), or lower the internal barriers to the structural re-arrangement ofa product (e.g. Duvernay et al. 2005, in the case of the isomerization of cyanamide). It is there-fore plausible that some of the gas-phase activation energies used in this model over-estimate thebarriers in the solid phase; however, such effects are difficult to quantify without a specific com-putational or experimental study of each solid-phase reaction and its low-temperature tunnelingcharacteristics.For self-consistency, all reactions of surface radicals with complex species are now assumed ∼
114 monolayers; this would result in a UV field strength at the deepest ice layer of ∼
45% of thevalue at the surface. This corresponds to a mean value of 69% of the assumed field strength, forthe ice mantle as a whole. However, the ices formed on interstellar dust-grain surfaces constitutea mixture of various molecular species, and the absorption cross-sections for many of these arecurrently unknown or poorly defined.No desorption processes are allowed from the bulk ice; thus desorption of these species mustproceed via a prior transfer of material from mantle to ice surface. Reaction–diffusion competitionis also included for reactions mediated by activation-energy barriers (following G&P), for bothsurface and bulk-ice reactions; this is perhaps the largest departure from the methods of GWH, asthis change can produce reaction efficiencies many orders of magnitude different from the simpleArrhenius treatment of previous models.Surface desorption processes included are thermal evaporation (as defined by the binding/desorptionenergy, E des ), reactive desorption as described by Garrod et al. (2007), and photo-desorption us-ing measured rates determined by Oberg et al. (2009c,d); following G&P, all surface species areassumed to photodesorb with an efficiency of 10 - , in the case where values are not provided bythose authors.The indirect mechanism for CO formation proposed by G&P is also included for reactionsboth on the surfaces and within the ice mantles.The reproduction of the high observed abundance ( ∼ - with respect to H ) of methyl for-mate (HCOOCH ) in hot cores has proved somewhat problematic in previous astrochemical mod-els. Garrod & Herbst (2006) showed that grain-surface formation mechanisms could produceadequate quantities of methyl formate (MF) to explain observations; however, in some cases itwas found (Garrod et al. 2008; Belloche et al. 2009) that the evaporation of MF at relatively low 10 –temperatures could result (dependent on the warm-up timescale) in only a small fraction of thismaterial surviving the transition to the gas-phase. Belloche et al. (2009) adopted a higher bindingenergy for MF (5200 K vs. 4100 K), citing the importance of hydrogen bonding in the estimationof this value; they found that this value produced results appropriate to observational abundancevalues for methyl formate. This value is also adopted here. Table 4 shows a selection of otherbinding energies used in the present model. As found by GWH and Laas et al. (2011), the rates and branching ratios of methanol pho-todissociation in the ice mantles are crucial to the production rates and ratios of various complexorganic molecules detected in hot cores, as the ice-mantle methanol provides a large supply ofstructurally-complex organic material.The present model uses the methanol branching ratios derived from the experiments of Oberget al. (2009a) for products [CH OH+H]:[CH O+H]:[CH +OH] of 5:1:1. In the absence of otherinformation, these values are applied to both the direct UV photodissociation by the interstellarradiation field, and to photodissociation by the secondary UV photons produced by cosmic rays,the latter of which is most important at the high visual extinctions of the hot-core phase. Theseratios are applied throughout to the ice and gas phases, although, as found by Laas et al. (2011), theimportance of gas-phase methanol photodissociation to complex molecule production is minimal.Activation-energy treatments for CO and H CO use best-fit expressions to uni-molecularand bi-molecular rates recently acquired through quantum transition state theory (Goumans, priv.comm.; Andersson, priv. comm.). Hydrogen abstraction from H CO and CH OH are included,mediated by activation energy barriers, while hydrogen abstraction from HCO and CH O/CH OHare also allowed (producing H + CO/H CO), assuming branching ratios of 1:1 with the associatedhydrogen-addition channels (i.e. no activation energy).
A number of potential routes have been suggested in the literature for the formation of glycinein interstellar ices, based on laboratory evidence or theoretical considerations. Experiments byBernstein et al. (2002) and Muñoz Caro et al. (2002) showed that UV irradiation of interstellar iceanalogs containing H O, CH OH, CO, CO , NH and/or HCN could produce significant quantities 11 –of amino acids, including glycine. Sorrell (2001) had suggested a route involving the reaction of theNH radical with acetic acid (CH COOH), itself formed through the addition of CH and HOCO,while Woon (2002) suggested that the addition reaction between radicals NH CH and HOCOcould explain the formation of glycine, with these species produced in the ices by successivehydrogenation of HCN and by the addition of CO to OH, respectively. Experimental work byHoltom et al. (2005) involving the electron bombardment of CO /NH CH ices confirmed theviability of Woon’s mechanism. Elsila et al. (2007) found Woon’s mechanism to be consistentwith the origins of the nitrogen and central carbon in the glycine molecule, while the origin of theacidic carbon was more consistent with the formation of glycine occurring via a nitrile precursor,i.e. amino acetonitrile (NH CH CN).Here, we include a number of new radical-addition reactions relating to glycine and similarspecies. Each hydrogenation step suggested by Woon (2002) is included, although all but the finaladdition of NH CH + HOCO was already present in the network. However, other routes arealso included, such as the addition reaction NH CH + HCO → NH CH CHO (glycinal), whoseproduct may (for example) be photodissociated to produce the radical NH CH CO, which mayfurther react with OH to produce glycine. There are four final processes that lead to glycine in thisnetwork, H + NHCH COOH → NH CH COOH (5)NH + CH COOH → NH CH COOH (6)NH CH + HOCO → NH CH COOH (7)NH CH CO + OH → NH CH COOH (8)although there are several ways in which each radical may come to be formed, either throughchemical reaction or by photodissociation of a stable molecule. Reaction (5) is also complementedby exothermic radical-radical reactions with species (e.g. HCO) that may donate a hydrogen atomto form two stable molecules, as described in section 2.2. Reaction (5) typically follows the pho-todissociation of, or H-abstraction from, glycine itself; reactions (6)-(8) are thus the major potentialformation routes.Woon suggests the formation of HOCO by the reaction of CO and OH. This process is difficultto model accurately, due to the complex nature of the transition states; the reaction may also leadto the formation of CO + H (see G&P, and references therein), or may dissociate back to CO +OH, dependent on the rapidity of energy loss to the surface. As such, the OH + CO reaction ismodeled separately for each set of products, assuming an activation energy barrier of 2500 K forthe HOCO branch, following the approach of GWH. In practice, the formation of HOCO in themodel is dominated by the photodissociation of or chemical hydrogen abstraction from formic acid(HCOOH) in the ice, which is formed predominantly by HCO + OH additions (see GWH). 12 –Also included in the model is a selection of species similar to glycine, but with alternativefunctional groups. For example, glycinal (NH CH CHO) and propionic acid (C H COOH) aremodeled, through analogous reactions to those of glycine, while new dust-grain formation routesare added for propionaldehyde (or propanal, C H CHO), which has been detected toward SgrB2(N) (Hollis et al. 2004). The inclusion of these other species ensures that the importance ofreactions leading to glycine formation is not over-estimated due to the omission of competingreaction pathways.
As for other complex species, the chemical network includes gas-phase destruction routesfor glycine that consist of UV photodissociation, either by the cosmic ray-induced or standardinterstellar radiation field, or by reactions with atomic or simple molecular ions. Table 5 shows thenewly-included reactions for glycine and its related gas-phase products. Electronic recombinationof protonated glycine results in the re-formation of glycine with an efficiency of 5 %, but all theglycine in the gas-phase is originally formed on the grains. Consideration of a potential gas-phaseformation route is given in the models of Section 5.
The physical model used here broadly follows that of G&H and later papers, in which acollapse phase is followed by a static warm-up phase. In the first phase, the density increases from n H = 3 × to 10 cm - , under the free-fall collapse expression given by Nejad et al. (1990).However, in contrast to previous hot-core models, while the gas temperature is held at a constant10 K, the temperature of the dust varies with visual extinction, according to equation (17) of G&P,which describes the heating of the dust by the interstellar radiation field, assuming a dust-grainradius of 0.1 µ m. At the initial visual extinction of A V = 2, the dust temperature is ∼
16 K; duringcollapse, this falls to a minimum temperature of 8 K.During the subsequent warm-up phase, the core is heated from 8 – 400 K, with density heldat 10 cm - . Three warm-up timescales are adopted, which are the same as previous models, inso far as they reach 200 K at the same point in time (Table 6). However, the warm-up is extendedbeyond this time, until 400 K is reached, so that the later evaporation and gas-phase behavior ofmore strongly-bound species, such as glycine, may be studied over a longer period. During thewarm-up phase, gas and dust temperatures are assumed to be well coupled due to the high density;the gas kinetic temperature follows that of the dust grains when T dust >
10 K. Table 6 shows the 13 –details of the three warm-up phase physical models.Table 7 shows the composition of the dust-grain ices at the end of the collapse phase (corre-sponding to the starting values for each of the following warm-up models), as well as observationalvalues for comparison.
3. Results
Figures 1, 2 and 3 show the behavior of fractional abundances with respect to total hydrogen( n H ) of a selection of simple and complex molecules, for the fast , medium and slow warm-up mod-els, respectively. Peak gas-phase abundances are shown in Table 8, along with the correspondingsystem temperatures for each peak value, which frequently correspond to the temperature of peakevaporation for species formed on the dust grains.In Figs. 1 – 3, panel (a) shows some of the main ice constituents and a representative ion,HCO + . Panels (b) and (c) show some complex organics typically observed toward hot cores. Panel(d) shows some commonly observed nitrogen-bearing species as well as the as-yet undetectedhydroxylamine (NH OH). Panel (e) shows a selection of complex species containing a carbonylgroup (C=O), including acetone, (CH ) CO. Panel (f) shows complex species derived from thelarger photo-fragments of methanol. Panel (g) shows a selection of complex organics bearingan amine group (NH ), while panel (h) shows glycine itself (NH CH COOH) along with severalsimilar or related molecules. Not all species shown in Table 8 are plotted in Figs. 1 – 3.The results for a selection of important species and their progenitors are discussed in detailbelow. Due to the large number of molecules included in the model, the results for many moleculesare presented in Figs. 1 – 3 and Table 8 without comment. For a description of the most importantreaction mechanisms relating to these species, the reader is referred to the analysis presented byGarrod et al. (2008); however, some general differences between the current and previous modelsare discussed in section 6.
Glycinal (NH CH CHO) is the amino aldehyde corresponding to the amino acid glycine. Itsformation in these chemical models, shown in panel (h) of Figs. 1 – 3, begins at around 25 K, whenthe radical HCO becomes mobile and reacts with CH NH . The latter species is formed by thehydrogenation of CH NH, which builds up at around 15 K via the addition of NH and CH radicals. 14 –The HCO radical is mainly formed by the abstraction of hydrogen from formaldehyde (H CO) byOH, which is a barrierless process; this occurs until formaldehyde evaporates at around 40 K (seeG&H, GWH, and section 3.2, below). A later and somewhat stronger glycinal formation routeoperates at ∼
40 K, when NH radicals add to CH CHO radicals formed by the photodissociationof acetaldehyde (CH CHO).Glycinal formation thus occurs at rather lower temperatures than that of glycine (see below).However, both are at least partially dependent on the earlier formation of acetaldehyde at lowertemperatures to provide the CH CO structure present in both. Peak gas-phase glycinal abundancesare a few 10 - to 10 - with respect to total hydrogen; it is thus of similar abundance to the moreprevalent observed organic molecules in hot cores. No mm/sub-mm spectral information is appar-ently available for glycinal at present. Glycine formed on the grains is seen to be released into the gas phase at a temperature ofaround 200 K, attaining a peak gas-phase abundance of 8 . × - , 4 . × - , and 8 . × - with respect to total hydrogen (see Table 8 and Figs. 1–3 panel h), for the fast , medium , and slow warm-up timescales, respectively.The three main production routes included for glycine (Eqs. 6 – 8) are all active, and allcontribute a proportion of the glycine later released into the gas phase. Significant dust-grainsurface/mantle formation of glycine begins at temperatures of 40 – 50 K, and may continue up toaround 120 K.For the medium warm-up timescale case, at around 40 K the OH radicals in the ice, producedby the photodissociation of water molecules, are sufficiently mobile to find glycinal (NH CH CHO),which is abundant at around 10 - - - with respect to total hydrogen. The OH radical easily ab-stracts a hydrogen atom from glycinal; the activation energy barrier is sufficiently low (591 K)compared to the diffusion barrier for OH that the reaction occurs before OH has an opportunity todiffuse away from its reaction partner. (This effect indeed confers an efficiency close to unity onmost such OH-initiated hydrogen-abstraction reactions). The resulting radical, NH CH CO, thenreacts with another OH to produce glycine (Eq. 8).At temperatures of 55 K and above, much greater quantities of glycine are formed; hydrogenabstraction from acetic acid (CH COOH) by NH radicals within the ice mantles and the sub-sequent addition of the resultant CH COOH radicals to NH produces glycine (Eq. 6). The NH radicals are primarily formed by hydrogen abstraction from ammonia (NH ) by OH radicals, whichare themselves formed by the photodissociation of water ice. The increased importance to glycine 15 –formation of the acetic acid-related path at these temperatures is caused by the greater abundanceof NH radicals that results from the evaporation of HNCO molecules from the ices, which up untilthat time represent a major reaction partner for NH . The release of HNCO into the gas phase maybe seen in Figs. 1 – 3, panel (d). However, over the 55 – 75 K range, Eq. (8) still dominates Eq. (6)by a factor of 2 – 3, as the greater availability of NH allows the NH CH CO radical to be formedby hydrogen abstraction from glycinal by NH as well as OH.At around 75 K, an ice surface (as opposed to mantle ) process becomes the strongest con-tributor to glycine formation; hydrogen abstraction from CH NH (methylamine) by OH radicalsproduces CH NH , while abstraction from HCOOH (formic acid) by OH produces HOCO. Thesereact to produce glycine (Eq. 7) on the ice surface, by the route suggested by Woon (2002). Thismechanism then competes roughly equally with the reaction of CH COOH and NH on the icesurface (Eq. 6) to be the main producer of glycine, up to ∼
90 K. By this point, most glycineformation is taking place on the surfaces of the ices, rather than within the ice mantles. This iscaused by the increasing rate of mantle-to-surface diffusion among less strongly-bound species,including NH , as the temperature rises, coupled with their commensurately faster reaction rateson the ice surface. The more strongly-bound products of these reactions, such as glycine itself,are “swapped” back into the deeper mantle following their formation, as they are exchanged withmore mobile, volatile species.Between around 90 – 120 K, the reaction of NH and CH COOH (Eq. 6) again takes over asthe dominant route to glycine on the grains, as CH NH is gradually lost to the gas phase, renderingEq. (7) far less effective.The majority of the glycine ultimately released into the gas phase is formed during the 90 –100 K period. During this time, Eq. (6) dominates Eq. (7) by a factor of ∼ ), formic acid (HCOOH), and aceticacid (CH COOH) evaporate fully from the grains, closing down the main glycine formation mech-anisms. From this point on, glycine begins to migrate from the bulk ice mantle into the surface,while suffering a moderate degree of attrition by hydrogen abstraction and photodissociation – theproducts of which typically evaporate.For the fast warm-up model, the temperature dependence of the formation mechanisms isbroadly similar; however, the importance of each route is different, due to the differing quantitiesof precursor molecules available. Most importantly, the abundance of acetic acid (CH COOH),shown in panel (e), is around one order of magnitude lower than in the medium timescale model. Asfound by Garrod et al. (2008), in these models acetic acid is formed predominantly by the additionof OH to CH CO, the product of the abstraction of hydrogen from acetaldehyde (CH CHO) by OHitself. The fast warm-up model allows a shorter time period for this process, before acetaldehyde 16 –evaporates from the grains, resulting in the lower acetic acid abundance. This in turn renders theproduction of glycine via Eq. (6) generally a factor of a few slower than Eqs. (7) & (8), which,overall, provide approximately equal amounts of glycine production in this model.For the slow warm-up model, the behavior of glycine production is much more similar to thatof the medium case; however, here the NH + CH COOH route is strongly dominant over the 60– 120 K range during which glycine production is important. This is caused by the greater timeperiod for the production of acetic acid. Production via Eq. (8) is also less significant than in thetwo shorter-timescale models, due to the lower abundance of glycinal in the ices.In all models, the gas-phase destruction of glycine is entirely dominated by protonation anddissociative electronic recombination, as is the case for the majority of complex organics (seealso GWH); photodissociation has only a small effect, as the only UV radiation field capable ofinfluencing the chemistry during the warm-up phase is that induced by cosmic rays.These models produce a low to moderate abundance of glycine in the gas phase, in comparisonwith other complex species produced in the models. The peak gas-phase abundance of glycineis also very similar to that of acetic acid in each model, albeit with a different temperature ofevaporation. The question of whether this glycine may be detectable is addressed in Section 5.
Amino acetonitrile (NH CH CN), or AAN, shown in panel (h), has been suggested as a pre-cursor to glycine (Elsila et al. 2007). It is formed in these models with a peak gas-phase fractionalabundance of a few 10 - to 10 - , consistently for each timescale model. This is around a factor oftwo higher than the values produced in the model of Belloche et al. (2009), and around a factor of10 greater than the value derived from observations toward Sgr B2(N) by Belloche et al. (2008).In these models, AAN is formed primarily by the addition of NH to the radical CH CN,which itself derives from hydrogen abstraction from CH CN molecules by NH at around 60 – 80K, producing an abundance of around 10 - on the grains. Later, at around 90 K, the evaporationof CH CN from the grains results in its gas-phase protonation and recombination with electrons,producing CH CN with an efficiency of 50 %. This radical re-accretes onto the grains, to reactwith NH , which produces an AAN fractional abundance of around 10 - on the grains. However,in light of recent measurements of methanol recombination branching ratios (e.g. Geppert et al.2006), it is unclear whether such a high efficiency of CH CN production by gas-phase electronicrecombination is realistic. A value of 5 %, as adopted in these models for the recombinationof more complex species, would render the earlier formation of AAN by purely grain-surfacechemistry the dominant mechanism, and would produce abundances close to the values observed 17 –toward Sgr B2(N).
Propionaldehyde (or propanal, C H CHO) and propionic acid (or propanoic acid, C H COOH)are structurally similar to glycinal and glycine, and neither have been treated in chemical modelspreviously. Propionaldehyde is formed in great abundance at low temperatures, by the addition ofHCO and C H radicals on the dust-grain ice surfaces; abundances as high as 10 - with respect tototal hydrogen are formed in the slow warm-up model. Production is most rapid at around 30 K,when the evaporation of grain-surface methane (CH , panel a) is fastest. This results in a signifi-cant increase in the abundance of gas-phase acetylene (C H ), which accretes onto the dust grains,where it is rapidly hydrogenated to C H , thence reacting to form propionaldehyde. Formation onthe ice surface at this time is sufficiently rapid that so-called reactive desorption, whereby the en-ergy released from the exothermic formation of a surface molecule results in desorption (e.g. Gar-rod et al. 2007), produces a gas-phase peak in the abundance of propionaldehyde of approximately10 - n H . This period of carbon-rich gas-phase chemistry associated with methane evaporation isoften labeled warm carbon-chain chemistry (WCCC), and has been identified observationally bySakai et al. (2008); however, it is unlikely that the enhancement in propionaldehyde seen in themodels would be observable at the low abundances predicted by these models. The large quantitythat remains on the grain surfaces later evaporates at around 120 – 130 K, producing gas-phasepeak fractional abundances of around 10 - . This molecule was detected by Hollis et al. (2004)toward Sgr B2(N); however, no specific abundance was determined.Propionic acid (C H COOH) is formed on the grains much later than propionaldehyde; mostproduction occurs from around 70 K onwards, by the addition of OH and C H CO radicals on theice surface. The latter species is formed primarily through hydrogen abstraction from propionalde-hyde by NH in the ice. Thus, propionic acid production appears to be directly dependent on theprior formation of its associated aldehyde. Methanol (CH OH) and formaldehyde (H CO), shown in Figs. 1–3 panel (b), are both presentin the dust-grain ice mantles in large quantities, following their formation at low temperature duringthe collapse phase (see Table 7). Formaldehyde remains the primary source of HCO radicals in the 18 –ices, due to hydrogen abstraction by OH, until it evaporates at around 40 K, producing a significantgas-phase peak – see G&H and GWH. This feeds the gas-phase formation of other species, mostnotably formic acid and methanol.Methanol abundance in the ice is essentially static until it eventually evaporates at around 120K. But methanol nevertheless provides the majority of organic structure for the formation of morecomplex molecules, in the form of methyl (CH ), methoxy (CH O) and hydroxymethyl groups(CH OH). These are formed primarily by photodissociation caused by the cosmic ray-inducedUV field that penetrates the hot core. Above ∼
45 K, OH radicals become mobile, and hydrogenabstraction to form CH OH becomes the dominant destruction mechanism for methanol, producingaround twice as much CH OH as the photodissociation route.The abundance of methanol in the ices is little affected by the warm-up timescales of eachmodel. The fall in the gas-phase abundances is more significant, but the apparent differences be-tween each timescale model are mainly due to the longer timescales over which the chemistryof the slower warm-up models is simulated, rather than to a difference in the rate of destruc-tion. The temperature–abundance relationships may, however, be important to the interpretation ofobservationally-determined abundances and rotational temperatures. The apparently precipitousfall in the gas-phase abundances of various other molecules in the slow warm-up model is alsolargely attributable to the longer timescales adopted in that model.The eventual evaporation of methanol also indirectly produces a high-temperature peak informaldehyde abundance; the reaction of methanol with protonated methanol produces protonateddimethyl ether (CH OCH + ), one of whose electronic recombination products is assumed to beformaldehyde in this model. The branching products of this process are not well constrained, pace Hamberg et al. (2010), who indeed do not identify H CO as a likely product. The secondary peakin formaldehyde abundance may at least be considered unreliable, due to these uncertainties.
The peak abundance of methyl formate (MF, HCOOCH ), shown in Figs. 1–3 panel (b), isin line with that expected from observations (around 10 - n H ), except for the slow warm-up model.The evaporation of methyl formate prior to that of methanol and various other species leaves itvulnerable to destructive reactions with molecular ions, whose abundance would otherwise belessened by the presence of other reaction partners. The long timescale between methyl formateand methanol evaporation in the slow model therefore leads to significant methyl formate destruc-tion; a similar result was noted by GWH and Belloche et al. (2009), in the case of a lower assumedMF binding energy. 19 –Methyl formate is formed entirely on the dust grains in this model, by the reaction HCO +CH O. Production is mainly within the ice mantles, peaking at 25 K, although significant produc-tion also occurs on the ice surface.Glycolaldehyde (CH (OH)CHO), shown in Figs. 1–3 panel (c), is formed similarly to its astructural isomer methyl formate, via HCO + CH OH. Its gas-phase and ice abundance is greaterthan that of MF, due to the more rapid production of CH OH over CH O – by a factor of 5 (forphotodissociation) in this model. Observations of protostellar envelopes, however, do not demon-strate this large abundance of glycolaldehyde; the recent detection by Jørgensen et al. (2012)toward the Class 0 protostellar binary IRAS 16293-2422, using the ALMA telescope, indicated aHCOOCH :CH (OH)CHO ratio of 10 – 15 (although the observational glycolaldehyde rotationaltemperature of 200 – 300 K is consistent with the present model results).The discrepancy may be related to the assumed branching ratios of the reactions betweenHCO and either CH O or CH OH:HCO + CH O → HCOOCH ( -
423 kJ / mol) (9a) → CO + CH OH ( -
372 kJ / mol) (9b) → H CO + H CO ( -
292 kJ / mol) (9c)and HCO + CH OH → CH (OH)CHO ( -
290 kJ / mol) (10a) → CO + CH OH ( -
276 kJ / mol) (10b) → H CO + H CO ( -
197 kJ / mol) (10c)(The enthalpy change associated with each reaction, ∆ H f , is indicated in brackets). The branchingof each set of reactions is assumed to be [1:1:1] in these models. Each branch of equations (9) and(10) is exothermic, and branches (a) and (b) would require minimal internal re-arrangement. Thesingle-product routes in each case are the most exothermic; however, in the case of glycolaldehydeformation, the enthalpy change related to reaction branch (10b) is close to that of (10a). While theassumed efficiency of branch (c) (i.e parity with the other two branches) may be over-estimatedin both equations (9) and (10), the production of CO and CH OH (10b) may be very competitivewith the formation of glycolaldehyde (10a), while it may be less so in the case of methyl formate.It thus appears plausible, by this simplistic analysis, that a difference in the efficiencies offormation of MF and glycolaldehyde via their primary grain-surface/ice-mantle formation routescould account for the order-of-magnitude discrepancy in observational abundances. However, adetailed theoretical determination of the branching behavior of these reactions in the solid phasewould be necessary to confirm this theory. Alternative branching ratios in the photodissociation 20 –of methanol, to produce a significant excess of CH O over CH OH is also possible, although thecurrent – and only – estimate of these values for solid-state methanol, based on experimental rate-fitting, suggests precisely the opposite relationship (CH O:CH OH of 1:5; Öberg et al. 2009a).A decrease in the efficiency of glycolaldehyde production as described above would be un-likely to affect significantly the abundances of other observed species, although the production ofpostulated molecules related to glycolaldehyde, such as dihydroxyacetone (HOCH COCH OH)could be affected. The destruction rates of the HCO and CH OH radicals would remain the same,while the increased re-formation of CO and CH OH resulting from the alternative product branchwould have only a minor effect on the already large abundances of those species.The glycine formation routes included in this model are sufficiently independent from theglycolaldehyde chemistry that glycine production would also be unaffected by the adoption of analternative efficiency for glycolaldehyde formation. Similarly, while acetic acid (CH COOH) isa structural isomer of both glycolaldehyde and methyl formate, its different structure means thatits formation routes are not directly related to those of its isomers; the choice of treatment forglycolaldehyde would there have little effect on its own abundance or, through it, that of glycine.The chemical behavior of acetic acid is discussed above, in section 3.1.1.
Formic acid (HCOOH), shown in Figs. 1–3 panel (b), is formed to a large degree in thegas phase, especially for the fast and medium warm-up models; this occurs when formaldehyde(H CO) evaporates at ∼
40 K, reacting with OH to form HCOOH and atomic hydrogen. Thegas-phase formic acid accretes back onto the grains, and does not evaporate until a temperature ofaround 120 K is reached. A similar or somewhat smaller quantity of the formic acid that ultimatelyevaporates from the grains is formed at low temperature within the ice mantles by the addition ofHCO and OH, as HCO becomes mobile.As such, it is unclear whether the formic acid observed toward hot cores originates in the gasphase or on the grains. As discussed above for the case of methyl formate and glycolaldehydeproduction, a plausible alternative product branch for the reaction of HCO and OH exists, yieldingCO and H O (rather than HCOOH); indeed, this branch is somewhat more exothermic than thesingle-product branch. Both branches were included in the model, at a 1:1 efficiency ratio. Thetrue efficiency for HCOOH formation could therefore be twice as large, or significantly smallerthan assumed. The rate of the gas-phase reaction (OH + H CO → HCOOH +H) is reasonably wellknown, albeit only around room temperature (Yetter et al. 1989, and references therein); but theamount of formic acid formed as a result is strongly dependent on the amount of formaldehyde 21 –that is released into the gas-phase from the grains.
The behavior of the amino aldehyde formamide (NH CHO), shown in Figs. 1–3 panel (d),is somewhat different to that presented in the models of GWH. In this case, the quantity formedin the ices, via the addition of HCO and NH radicals, is somewhat larger than previously found.However, its peak gas-phase abundance is lower, and falls over time, rather than rising as was foundby GWH. The latter change in behavior is due to the removal of a single gas-phase reaction fromthe network: NH + H CO → NH CHO + H. This reaction was present in previous networks witha generic collisional rate coefficient of 10 - cm s - , but it is likely to have an activation energybarrier (based on the barrier of 5.89 kcal/mol ( ∼ + HCO). The analogous reaction OH + H CO → HCOOH+H, discussed above, has a measured rate of 2 × - cm s - , corresponding to a maximum 2%efficiency in the branching ratio compared to the alternative H O + HCO branch. A theoreticalstudy (Li & Lu, 2002) of the NH + H CO → NH + HCO reaction suggested a rate coefficient of5 . × - cm s - . For these reasons, the NH + H CO reaction was removed entirely.
4. Gas-phase routes to glycine formation
While laboratory experiments have shown success in producing glycine and other amino acidsby the photolysis of organic ice mixtures (Bernstein et al. 2002; Muñoz Caro et al. 2002; Holtomet al. 2005; Elsila et al. 2007), gas-phase mechanisms for amino-acid production have also beenconsidered. Blagojevic et al. (2003) demonstrated that reaction between acetic acid (CH COOH)and ionized or protonated hydroxylamine (NH , OH + ) can result in the formation of ionized or pro-tonated glycine (NH , CH COOH + ) and water. Similar schemes involving propionic (propanoic)acid were found to produce the equivalent forms of alanine. The authors estimated rate coefficientsof > - cm s - for each of these processes.The most probable source of NH , OH + ions in hot cores would be NH OH, either by pho-toionization, electron transfer with atomic ions such as He + and C + , or protonation by proton donorssuch as H + , H O + or HCO + , all of which processes are already present in the chemical network.Protonation by CH + , as suggested by Snow et al. (2007), is not included; however, H + and H O + are around 2 orders of magnitude more abundant than CH + in the models, while the protonationrate coefficients in each case are typically very similar. Protonation rates of hydroxylamine byHCO + , H + and H O + of (0 .
59, 1 .
39 and 6 . × - ( T /
300 K) - . cm s - , respectively, are used 22 –in the model.Electronic recombination of both ionic and protonated glycine were already added with therest of the glycine-related chemistry; ionization and protonation, with subsequent electronic re-combination, are the primary destruction routes for glycine in all the models. Glycine is assumedto form in 5 % of recombinations of protonated glycine (in line with values adopted for otherspecies and with recent experimental determinations for protonated methanol and dimethyl ether),with a generic total recombination rate coefficient of 3 × - ( T /
300 K) - . cm s - . The samerate is assumed for the recombination of ionized glycine; the ejection of a hydrogen atom is againassumed to occur for 5 % of reactions, producing the radical HNCH COOH. This may accreteonto the grains to be directly hydrogenated, or may react with a selection of hydrogen-bearing gas-phase species, such as HCO, to produce glycine, as outlined in section 2.2 (although the influenceof these routes on glycine abundance is neglible). Various other gas-phase and grain-surface de-struction mechanisms are also available for the HNCH COOH radical, including photodissociationand further ion-molecule destruction processes.Formation of both hydroxylamine (NH OH) and acetic acid (CH COOH) occurs on the dust-grains in this model, and each reaches peak gas-phase abundance at around 130 – 140 K, followingevaporation. In order to test the gas-phase production of glycine from these species, both of thefollowing reactions are added to the network, assuming a rate constant of 10 - cm s - for each:NH OH + + CH COOH → NH CH COOH + + H O (11a)NH OH + + CH COOH → NH CH COOH + + H O (11b)Neither of these processes was included in the models already analyzed in section 3.
With the simple addition of reactions (11), the results are unchanged; the contribution of thegas-phase processes is never remotely significant compared to those on the dust-grains, in spite ofthe availability of both reactants at similar times/temperatures.It is noteworthy that the abundances of NH OH acheived in the current models are around 3orders of magnitude lower than those calculated by GWH; the reason for this is that the major for-mation route for NH OH on the grains is the addition of surface/ice-mantle NH and OH radicals.The availability of both these reactants is significantly curtailed in the present model by the inclu-sion of new hydrogen-abstraction reactions for these species (see Table 3) and by the more accurateconsideration of the kinetics of grain-surface reactions that are mediated by activation energy bar-riers (see G&P); each reactant is more readily converted back to H O or NH before the OH and 23 –NH radicals are able to meet. A recent observational search by Pulliam et al. (2012), using theNRAO 12 m telescope, detected no NH OH toward a range of previously-observed sources, withfractional abundance upper limits of 8 × - toward Sgr B2(N). The authors noted that emissionfrom a region more compact than 5 arcsec would not be detectable with their instrument, while themodel suggests that the NH OH would be at least as compact as typical hot-core molecules suchas methyl formate or ethanol, based on evaporation temperatures. Nevertheless, the new modelresults for NH OH are more in line with the observational data.However, a recent laboratory study suggests that the formation of NH OH by successive grain-surface hydrogenation of NO is extremely efficient (Congiu et al. 2012). While hydrogenation ofNO and HNOH are already present in the network, the reaction of H with HNO has until now beenassumed to lead to H-abstraction, with a barrier of 1500 K.To increase the effect of the glycine-forming gas-phase reactions, a parallel branch is addedto the surface/ice reaction set: H + HNO → HNOH. A barrier of 1500 K is also assumed; but atlow temperatures, the reaction competes effectively with hydrogen diffusion, producing a reactionefficiency that is close to unity. As a result, large amounts of NH OH are formed, in this caseduring the cold collapse phase, rather than the warm-up phase. A total fractional abundance of8 × - is present in the ice by the end of collapse, i.e. as the starting point for the warm-up phase(see Table 7). This agrees well with the cold-cloud models presented by Congiu et al. (2012).In order to further increase the influence of the gas-phase mechanisms, the rate coefficient ofreaction (11a) is increased to 10 - cm s - , a plausible maximum value for this reaction.The results of this optimized model are shown in Fig. 4. The large quantities of NH OHpresent in the dust-grain ices alters the fractional abundances of various species in the model by asmall degree, although with a negligible direct effect on the production of glycine within the ice.The abundance of glycine is in fact slightly reduced, as a result of the somewhat lower quantityof acetic acid present in the ice. The destruction of gas-phase acetic acid is rather faster in thismodel, due to reaction (11a). However, when compared to an identical model with reaction (11a)switched off (not shown), the contribution of the gas-phase reaction to the total glycine formed inthis model is around 2 % of the total formed on the grains. Some of the glycine that is formed inthe gas phase is re-accreted onto the grains, to evaporate later with the rest, while the remainderis destroyed by ion–molecule reactions. The immediate impact on gas-phase glycine abundanceby the newly-included mechanisms may be seen in the small bump at around 130 K; less than10 - n H is produced. It may be noted that, if no glycine-production mechanisms of any kind wereactive in the ices, and all production thus depended on the gas-phase route, two abundance peakswould likely occur, at 130 K and 200 K, corresponding to peak production and peak evaporation,respectively. 24 –On the the basis that this scenario represents the optimal conditions for gas-phase glycineformation to occur in a hot core (including the use of a very optimistic reaction rate), it appearsthat the particular gas-phase formation mechanism tested is unlikely to be significant, especiallyif the mechanisms for formation within the dust-grain ice mantles are in operation as suggestedby the model. The plausibility of such a large hydroxylamine abundance as would be required forsignificant glycine production is also discussed in Section 5.3.
5. Spectroscopic modeling
In order to compare the model results more directly with observations of specific sources,a spectroscopic model is constructed that combines observationally-determined temperature anddensity profiles with the temperature-dependent chemical outputs of the model, to simulate emis-sion from a selection of key molecules for which observational data exist toward the given source;this simulated emission is then convolved to allow direct comparison with the observed spectraldata.
The warm-up phase of the chemical model produces molecular fractional abundances for pre-defined output times, each corresponding to a temperature. The resolution of these output times ischosen such that the associated temperature values are separated by less than 1%, over the 8 – 400K range. van der Tak et al. (2000) provide such physical profiles for the envelopes of 14 nearbyhigh-mass protostellar sources. Using these temperature–radius and density–radius relations, aradius and density is assigned to each temperature value in the chemical model outputs. Thefractional abundance of each species in the model at each temperature/radius value is multipliedby its local density, to produce an absolute abundance value measured in cm - . The resultingmolecular number-density and temperature profiles are then used to calculate the emission andabsorption coefficients at each spherically-symmetric radial position in the core.Partition functions and emission-line data from the JPL line list and the Cologne Databasefor Molecular Spectroscopy are imported into the code as needed, using the ‘Splatalogue’ onlinedatabase. The spectral coefficients may be calculated by this method to incorporate all molecularemission at any given frequency, allowing line blends and line confusion to be taken into account.Gaussian line profiles are assumed, using observationally-determined line widths. A channel width(frequency-bin size) much smaller than the line width is chosen (in general, 0.1 MHz or ∼ I ν ( s ) = I ν (0) e - τ ν ( s ) + Z τ ν ( s )0 B ν ( T ( τ )) e - τ ν d τ (12)where I ν is the specific intensity, τ ν is the optical depth at frequency ν , T is temperature, s is theline-of-sight distance, and B ν ( T ) is the Planck function (equal to ǫ ν / κ ν , under LTE). Using the grid-ded, spherically-symmetric input data, this equation is integrated numerically along lines of sight(using Simpson’s rule), beginning directly on-source, and moving outward through parallel linesof sight until a user-defined maximum offset is reached. Line-of-sight integrals of the absorptioncoefficient similarly yield the optical depths. This procedure results in an intensity map of the hotcore for each frequency channel.The final step is to convolve the emission with a Gaussian beam centered on the source, usinga beam-size appropriate to a chosen instrument observing at a given frequency. The intensity mapis numerically integrated with the Gaussian function, over the radius of the hot-core envelope, outto a few beam widths. The technique automatically accounts for beam-dilution, and makes useof the precise emission structure to calculate an intensity value at each frequency. The resultingsimulated spectrum may be directly compared with main-beam temperature ( T mb ) spectra obtainedfrom the telescope for which the convolution has been produced. The molecular mm/sub-mm line emission from a selection of the sources observed by van der Tak et al.(2000) was surveyed by Bisshop et al. (2007) using the James Clerk Maxwell and IRAM 30 m tele-scopes, providing information on dozens on complex organic species. A member of this subset,the hot-core source NGC 6334 IRS1, is relatively closeby (1.7 kpc), and exhibits relatively narrow( ∆ V = 5 km/s), strong emission lines (see van der Tak et al. 2000 and Bisschop et al. 2007, andreferences therein). It is also well situated in the sky (Dec. (1950) = -35 ◦ ◦ ). For these reasons, it may be identified as a plausiblecandidate for the future detection of glycine. The spectroscopic model described above is thereforeused to assess the potential for the detection of glycine in this source, on the assumption that its for-mation and subsequent behavior are well described by the chemical model. The physical profiles splatalogue.net
26 –provided by van der Tak et al. (2000) are used. In the case of glycine, only emission lines whosefrequencies are within the observable ranges of the JCMT, IRAM 30 m and ALMA telescopes aremodeled.Fig. 5 shows – for illustrative purposes – the predicted emission from this source over the241.350 – 241.425 GHz range, using a channel spacing of 0.488 MHz. These spectral calculationsconsider emission from all species in the model for which spectroscopic data exist, using onlyground-state transitions. Glycine emission, at 241.373 GHz, is highlighted in red; glycine con-former I is simulated, but not conformer II, due to uncertainty in the partition functions. The upperpanel of the figure shows the unconvolved emission for an on-source line of sight – the spectrummay be considered as that expected from a pencil beam of infinite resolution directed at the source.Individual lines are identified in the upper panel; an identification is made where more than half ofthe emission within a channel derives from a single molecule. The emission from glycine is seento be slightly blended with emission from glycolaldehyde (CH (OH)CHO) in the line wings, butnevertheless shows a clear peak. The middle panel shows the spectrum after convolution of theemission from the entire source (same temperature scale) using a beamwidth of 0.4 arcsec, whichencompasses the strongest predicted emission region for glycine (see below) and which should beachievable with ALMA at these frequencies (although the simulation is for a single-dish telescope,rather than an array). The glycine peak is preserved, with a line strength on the order of 1 K.The lower panel of the figure shows the predicted spectrum (different temperature scale) using abeamwidth appropriate to the James Clerk Maxwell Telescope at these frequencies ( ∼ convolved emission spectra is much more time-consuming. The consideration of the detectabilityof each glycine line in the following analysis therefore does not consider potential line blends –simply the expected line strength. More detailed assessments of the expected line emission fromvarious species will be made in future work.Fig. 6 shows the emission profiles predicted for the line center of a strong methyl formateline (left panel) and a strong glycine line of similar frequency (right panel; glycine emission isalso shown in left panel for direct comparison). The local emission strength (i.e. assuming a 27 –pencil beam) is shown in terms of brightness temperature for lines of sight targeted on radialdisplacements from the source position on the sky. Figure 7 shows the same profiles mappedonto sky coordinates; these emission maps are then convolved with the beam to produce simulateddetected brightness temperatures. The most significant emission from methyl formate is seen toemanate from a region of diameter ∼ ∼ ∼ ∼ Tables 9, 10 and 11 show details of the predicted emission from each molecule, using modeloutputs corresponding to the fast , medium and slow warm-up models, respectively. Line frequen-cies are shown in GHz, along with upper-level energies in K; in some cases, each ‘line’ representstwo or more lines of identical or very similar frequencies and/or spectral characteristics. Thecolumn marked ‘peak simulated local intensity’ indicates the maximum local emission strength(assuming a pencil beam). Beam widths represent the full-width half-maximum of the Gaussianbeam used; the precise beam width appropriate to the JCMT or IRAM 30 m is calculated by in-terpolation of telescope-specific data available online. The convolved intensity of the line is therelevant quantity for discerning the detectability of a line; however, for comparison with the ob-served lines, the integrated intensity (in units of K km s - ) provides a better test, as this quantityremoves the dependence on the average line width ( ∆ V ); this allows all of the emission predictedby the model to be compared against all of the emission detected in the observations. The final col-umn of these tables shows the integrated intensities measured for the methanol and methyl formatelines by Bisschop et al. (2007).It may be seen immediately that the simulated integrated intensities of the methanol lines arean excellent match to the observed values, being generally around a factor of 2 lower, and showingonly minor variation across the different warm-up timescale models. The simulations also providea good match regardless of the upper-level energies and beam sizes (which vary according tofrequency). The methyl formate emission is much more variable between model timescales; the fast model results provide an excellent match to all integrated intensities, falling within a factorless than 1.5 of the observed values. The medium timescale model produces values that are around2 – 3 times lower than those observed, similar to the agreement shown with the methanol lines.However, the slow warm-up timescale results produce integrated intensities only one hundredthpart as large as presented in the observations of Bisschop et al. (2007). In this case, methylformate suffers rapid gas-phase destruction, as described in Section 3.2.2, producing much lowerinstantaneous fractional abundances and much faster decline over time/temperature. The two faster 28 –warm-up models therefore appear the most favorable in comparison with observations. The tables show predictions for six of the strongest glycine lines, or suites of lines. Eachhas an upper-level energy sufficiently low to be well-populated at the 200+ K temperatures atwhich glycine fractional abundances are strongest in the models. The predicted intensities betweendifferent lines (within each model) are very consistent, and peak local intensities range from around1 K to 10 K, corresponding to fast and slow warm-up timescales, respectively. It is apparent thateven for this very nearby and otherwise favorable hot-core source, the glycine emission strengthis predicted to be very moderate; convolving the emission with a beam appropriate to the JCMT( ∼
20 – 22 arcesec) produces line strengths of no more than 10 mK in the most optimistic model.In the case of the fast warm-up model, which reproduces methyl formate emission most accurately,the glycine line strengths are no more than 250 µ K.Convolution of the emission using a beam appropriate to the IRAM 30 m telescope for eachline ( ∼
10 – 12 arcsec) produces line strengths of around 1, 3, and 30 mK, for fast , medium , and slow models respectively. This suggests that one of the strongest glycine emission lines couldplausibly be detected toward the given source using this instrument, assuming that the slow modelvalues are accurate; a 3- σ line detection would require a noise level of around 10 mK (assuming noline blending, which is not modeled here). However, detection assuming either of the other modelvalues would require impractical signal-to-noise values.In order to make an approximate estimate of the detectability of glycine using ALMA, thesame single-beam convolution method is used, along with two plausible, fixed beam sizes: ageneric 1 arcsec beam, and a 0.4 arcsec beam to match the size of the region of strongest glycineemission (see Fig. 6). The reduced beam-dilution produced in these cases results in much greaterline strengths, and suggests that the detection of a strong glycine line with ALMA is very plausible(line blending and model inaccuracies notwithstanding). The weakest emission predicted for anyof the simulated glycine lines, with a beam width of 1 arcsec, is ∼
87 mK, while at 0.4 arcsec theweakest line has a strength of ∼
350 mK. Under the optimistic slow warm-up model conditions,convolved line strengths are close to 10 K for the strongest lines, using the smaller beam. Forcomparison, the ALMA on-line sensitivity calculator indicates that, with 32 antennae (Cycle 1)and a resolution of 0.4 arcsec, ALMA would achieve an rms of 200 mK per 1 km/s velocity bin in1 hour. http://almascience.eso.org/call-for-proposals/sensitivity-calculator
29 –The line simulations therefore suggest that while detection of glycine using single-dish in-struments is unlikely, even for this very favorable source, detection with ALMA is highly plausible(ignoring possible line-blending effects). OH toward W3 IRS5
Pulliam et al. (2012) recently looked for hydroxylamine emission toward a selection ofsources including Sgr B2(N), Orion KL and W3 IRS5. They found no NH OH emission usingdata obtained with the NRAO 12 m telescope, with noise levels of a few mK. Both the GWHmodel and the enhanced NH OH model of section 4.1 exhibit large fractional abundances for thismolecule, albeit with different formation mechanisms in each case. In order to test whether themodel values are consistent with the non-detections of Pulliam et al., the spectroscopic model isagain applied to the chemical model results. Out of the sources observed by both Pulliam et al.(2012) and van der Tak et al. (2000), the only source present in both datasets is W3 IRS5. For thissimulation, a generic line width of 9 km/s is assumed, following Pulliam et al. (2012).Tables 12 and 13 show the results of a selection of NH OH emission-line simulations for W3IRS5, using, respectively, the standard medium warm-up timescale model results, and the resultsof the model of Sec. 4.1 that employs a gas-phase glycine formation mechanism and a large initialNH OH abundance on the grains, produced by the low-temperature formation of NH OH on dustgrains during the collapse phase. The results shown in Table 12 are all consistent with the non-detection; Pulliam et al. (2012) find a 1- σ noise level of 4.3 mK in their W3 IRS5 data, whilethe simulated intensities are of order 10 µ K or less. However, the model with enhanced NH OHformation produces maximum convolved line intensities of around 50 mK, or around 1 order ofmagnitude greater than the noise level.Since the simulated line strengths scale well with the peak fractional abundance of NH OHobtained in the chemical models, the observed values would require a peak gas-phase abundance of < - for the models to reproduce the non-detection of hydroxylamine, assuming all other param-eters in the models are correct. The implication for the models is that the cold-stage conversion ofNO/HNO to NH OH on the grains is too efficient, nominally by a factor of 10. This would suggestthat the gas-phase formation of significant quantities of glycine is also less probable, in all sources.The apparent over-estimate of hydroxylamine production could be explained by several possibil-ities; one is that the chemical network does not include a sufficent number of competing reactionmechanisms for all of the states of hydrogenation between NO and NH OH. Another possibility isthat the determination that the reaction H + HNO → H NO has an insignificant barrier, by Congiuet al. (2012), is dependent on experimental conditions that are inappropriate to these models, suchas the ice composition, which is predominantly water in the ISM. Alternatively, the hydroxylamine 30 –abundance in the ice may be adversely affected either by photo-destruction or hydrogen abstractionprocesses within the ice, whose rates or barriers may be inaccurately quantified in the models.
6. Discussion6.1. Dust-grain chemistry
The general behavior of complex molecules as simulated in the new models is broadly sim-ilar to that seen in the previous models, such as G&H and GWH; evaporation of grain-surfacemolecules into the gas-phase occurs around the same temperatures and in similar quantities. How-ever, the formation temperatures of molecules on the grains are somewhat different, due both tothe distinction between surface and ice-mantle populations and to the difference in diffusion ratesin each medium; HCO-related species are formed strongly around 25 K, while CH -related speciesare formed around 20 K – both somewhat lower than previous models, though more in line withrecent experimental results such as Öberg et al. (2009a).The interaction between the surface and ice-mantle chemistry in the models is complex; mo-bile radicals may land on the ice surface from the gas phase or may diffuse out of the mantle,to react to form more complex species, which show a net diffusion back into the mantle as morevolatile species move out. The migration of mantle species to the surface as temperatures increasetends to mitigate the ‘trapping’ effect that would be expected using a model in which there wereno surface–mantle diffusion. Much complex chemistry also occurs within the mantles themselves,particularly at elevated temperatures. The importance of mantle versus surface processes is de-pendent on the source of the reactants, the mobilities of the reactants, the temperature, and thegeneral composition of the surrounding ice; no general statement can therefore be made on thispoint other than that the diffusion within the ice mantles, and between the surface and the bulkice, appears to play a major part in hot-core chemistry. (Although the importance for specific,individual molecules is discussed in section 3).Aside from the effects of the differing treatment of the physical structure of the ices employedin this model, the inclusion of a more comprehensive set of hydrogen-abstraction reactions in theice chemistry also demonstrates the key role of water and OH in producing other free radicalswithin the ice that may go on to form more complex organic structures. The OH radical is highlyreactive, and may abstract hydrogen from stable molecules with only a small activation energy –typically lower than the barrier to OH diffusion. Thus, hydrogen abstraction by OH may occurwith a net rate equal to its rate of diffusion, in the case where the target molecule is less mobilethan OH. The large quantities of water present in the ice makes OH the most commonly producedphotodissociation product, caused by the weak, cosmic ray-induced, UV radiation that permeates 31 –the hot core.The complex molecules, such as glycolaldehyde (CH (OH)CHO), ethanol (C H OH) andmethyl formate (HCOOCH ), formed by the addition of HCO or CH to the photoproducts ofmethanol (CH OH) are produced early, at low temperatures, before OH becomes mobile (or abun-dant). Their production is therefore reflective of the direct photodissociation of methanol intoCH OH, CH O and CH .While greater temperatures increase OH mobility, below 40 K its primary destruction route(and the primary formation route for HCO) is the reaction OH + H CO → HCO + H O, whichis assumed to require no activation energy. The mobility of H CO itself drives the reaction, andit is not until H CO evaporates at around 40 K that OH becomes important in providing radicalsother than HCO. After this, HCO becomes less prevalent in the ices, while CH is still producedin some abundance by methanol photodissociation, resulting in a moderate bias toward methyl-group addition over aldehyde production. At this point, ammonia (NH ) and methanol, as majorconstituents of the ice, become the dominant reaction partners for OH, producing NH and CH OH(CH O is also produced, but the higher activation energy for this process renders it uncompetitiveversus the hydroxymethyl channel).It is therefore at temperatures above ∼
40 K that the formation of amino-organics becomesmost active, by addition of NH to methanol products, or to more complex radicals. However,at even higher temperatures, NH also becomes an important source of radicals in itself, as thebarriers to hydrogen abstraction by NH are relatively low compared to its diffusion barrier, as isthe case for OH. Above around 55 K, the photodissociation of water into OH typically results inthe subsequent conversion of ammonia to NH , which becomes the ultimate agent of hydrogenabstraction from organic molecules in the ice. This continues until ammonia, the source of NH radicals, evaporates at ∼
120 K.
The inclusion in the model of ice surface/mantle formation mechanisms for glycine indicatesthat it may be formed in a number of ways, whose degree of influence depends on the timescale ofthe hot-core evolution. The abundance of acetic acid (CH COOH) is perhaps most important in de-termining which mechanism is most important. In the slow warm-up model, acetic acid abundanceis relatively high within the ices, and the abstraction of hydrogen by NH , followed by the additionof another amine group, is the most important glycine-formation route. The same is true, albeitto a lesser extent, for the medium warm-up timescale model. The fast warm-up model producesless acetic acid, and the addition of CH NH and HOCO – products of OH-induced hydrogen ab- 32 –straction from methylamine and formic acid, respectively – becomes the major formation routein conjunction with OH addition to the NH CH CO radical, which is formed by abstraction fromthe amino aldehyde glycinal (NH CH CHO). It is questionable as to whether the high acetic acidabundances produced by the slow model are supported by observations, indicating both that glycineabundances may be lower than suggested by that model, and that no single ice surface/mantle pro-cess of the three that are tested in this work should be strongly dominant.It may also be noted that, in the case of the CH NH + HOCO glycine-formation route, aplausible alternative channel, producing CH NH + CO , may also be important. In this model abranching ratio of 1:1 is assumed; however, the accuracy of this assumption cannot be ascertainedwithout experimental or computational data for the solid-phase process (as opposed to the gas-phase equivalent, in which glycine production would be prohibitively disfavored). The effect of alower efficiency for glycine production through this method would be strongest in the fast warm-upscenario, although the availability of alternative routes means that glycine abundance is unlikelyto fall by more than a factor of 2 as a result; conversely, a more favorable branching ratio couldincrease the glycine production by a similar factor under fast warm-up conditions.A gas-phase mechanism for the formation of glycine was also tested in this model, consistingof the addition of protonated hydroxylamine (NH OH + ) and acetic acid (CH COOH), followedby electronic recombination. Even assuming the highest plausible rate, with large quantities ofhydroxylamine and acetic acid produced on the grains, the amount of glycine produced is only onthe order of 10 - n H , or 1% of the amount formed on the dust grains. The limited comparison ofsimulated NH OH emission with observations suggests that the actual fractional abundance mayindeed be lower than assumed in that model. It is possible that the fraction of dissociative recom-bination of protonated glycine that produce glycine itself may be somewhat higher than assumed(5%), but it is unlikely to be underestimated by more than a factor of a few. The combination offavorable conditions and rates that would be required therefore suggest that gas-phase productionby this method is unlikely to produce significant quantities of glycine.The possibility, demonstrated in the models, for significant glycine production to occur throughseveral distinct chemical routes suggests that the formation of glycine within the ice mantles is noless plausible than the formation of more commonly observed complex organic molecules.
The peak gas-phase fractional abundances for glycine of 8 × - – 8 × - produced by thechemical models suggest that this molecule could be reasonably abundant in regions within hotcores. However, the LTE radiative transfer and convolution models suggest that the detection of 33 –glycine toward a favorable source may be impossible with single-dish instruments, assuming anybut the most optimistic of the chemical models; this is due largely to the extremely compact emis-sion exhibited by glycine. The model findings are therefore in agreement with the current lack of adetection of this molecule. However, it appears that the new ALMA telescope will have sufficientsensitivity and spatial resolution to easily detect the strongest glycine emission lines, assumingthat the emission is not obscured by that from other molecules, and that the source is sufficientlycloseby that the highly compact glycine-emission region is well resolved. Detection will likelyrequire the careful choice of sources that are both nearby and that exhibit narrow emission lines.For this reason, detection toward the well-observed Galactic Center source Sgr B2(N) may bequestionable. While ALMA should allow the distinction of different structures within that source,which contribute to the considerable line widths (Belloche et al. 2008), it is not clear whether apredicted compact glycine-emission region (of temperature ≃
200 K) could be resolved sufficientlywell both to produce high enough line strengths for detection and to filter out contamination fromother molecules. No simulations – such as those produced above for other sources – are possible,due to the absence of both a temperature and density profile for Sgr B2(N) in the literature.The most important factor in the detectibility of glycine toward hot cores is likely to be itsbinding energy, which determines its evaporation temperature, and thus its radius of peak fractionalabundance. The simulations of glycine emission in NGC 6334 IRS1 suggest that the strongestglycine emission should emanate from a region ∼ The combined chemical and spectroscopic models produce a very good match with observedmethanol line emission toward NGC 6334 IRS1. The match for methyl formate is also good, in thecase of the two shorter-timescale models; warm-up timescales of around 1 Myr may not thereforebe appropriate to hot cores, although the precise binding energy of methyl formate is importantto this determination. The methyl formate results also indicate that, while other mechanisms mayplausibly exist for the formation of methyl formate in hot cores, the addition of methanol photo-fragments within the dust-grain ice mantles, as modeled here, appears adequate to explain observedabundances. Meanwhile, the structural isomer of methyl formate, glycolaldehyde, is almost cer- 34 –tainly over-produced, although this may be remedied by a more careful consideration of the productbranching ratios of the reaction between HCO and CH OH radicals in the ices. Branching ratiosfavoring an alternative [CO + CH OH] channel would seem plausible.All of the radiative transfer calculations presented here are highly dependent on the observationally-determined temperature–density–radius profiles provided by van der Tak et al. (2000). While thesimulations of methanol and methyl formate emission agree remarkably well with recent observa-tional data, the uncertainty in the profiles naturally increases at smaller radii, and the fidelity ofa spherically-symmetric model must inevitably break down where outflows or clumpy structurebecome important. Nevertheless, in the absence of more precise data, perhaps also to be providedby ALMA, the simple models used here provide a first quantitative estimate of the behavior anddetectability of glycine in star-forming regions. A more comprehensive assessment would also in-corporate the analysis of potential line blending, using spectroscopic models that include all speciesfor which data exist, as well as an explicit treatment to simulate interferometric observations whereappropriate.
7. Conclusions
The main conclusions of this work are summarized below:1. The hot-core chemical models predict peak gas-phase glycine abundances of ∼ × - –8 × - n H (dependent on warm-up timescale). The peak abundance values are attained ataround 200 K, when glycine evaporates from the dust grains.2. Glycine is found to form almost exclusively within or upon dust-grain ice mantles, beginningat temperatures of ∼ ∼
120 K. The three main radical–radical additionmechanisms investigated appear to have approximately equal influence on the resultant gas-phase quantities.3. Gas-phase glycine formation involving acetic acid (CH COOH) and protonated hydroxy-lamine (NH OH + ) is insignificant under even the most optimistic conditions.4. Related organic species such as propionic acid, propionaldehyde (propanal), and the aminoaldehyde glycinal are predicted also to attain significant gas-phase abundances, althoughtheir detectibility would be dependent also on their emission radii, via their evaporationtemperatures.5. The production of glycinal (NH CH CHO) and acetic acid (CH COOH) – two key moleculesin the formation of glycine in the ice mantles – are strongly dependent on the earlier produc- 35 –tion of acetaldehyde (CH CHO). Acetaldehyde and acetic acid could provide observationalinformation on potential glycine abundances in the absence of direct detection.6. The current lack of a detection of glycine toward hot cores may be explained by its hightemperature of evaporation, which results in a small emission radius. Glycine is not expectedto be detectable with single-dish instruments over realizable integration times toward anyhot-core source.7. The spectroscopic model suggests glycine may be detectable using ALMA at sub-arcsecondresolutions toward bright, nearby sources with relatively narrow emission lines, such as NGC6334 IRS1.8. Observed methyl formate abundances are well reproduced by the two shorter-timescale mod-els, indicating that grain-related formation mechanisms are sufficient (as suggested by previ-ous models), and that (8–400 K) warm-up timescales of around 1 Myr may be inappropriatefor hot cores.9. The anomalously high abundance produced by the models for the structural isomer of methylformate, glyclolaldehyde, may be remedied by the consideration of alternative branches forthe HCO + CH OH reaction in the ice mantles, favoring the formation of CO + CH OH.10. Cosmic ray-induced photodissociation of water ice, to produce OH, is crucial to the produc-tion of radicals within the bulk ices. The OH radicals easily abstract hydrogen from othermolecules, including ammonia, to produce reactive molecular radicals that may combine toform more complex species.11. NH , formed by hydrogen abstraction from ammonia by OH, also appears to be an importantagent of radical propagation within the ice mantles. This process, and the related productionof amino-organics, becomes most significant at temperatures between ∼ at thestart of the collapse phase. Species, i n i / n H † H . . - .
09C 1 . - . - . - . - . - . - . - . - . - . - † A ( B ) = A B
38 –Table 2. A selection of barrierless surface/mantle radical-addition reactions relevant to glycineor related species included in the chemical network
ReactionHOCO + CH NH → NH CH COOH → CH NH + CO NH + CH COOH → NH CH COOHOH + NH CH CO → NH CH COOHH + HNCH COOH → NH CH COOHCH OH + HNCH COOH → NH CH COOH + H COCH O + HNCH COOH → NH CH COOH + H COHCO + HNCH COOH → NH CH COOH + COHOCO + HNCH COOH → NH CH COOH + CO NH + CH COOH → HNCH COOHHCO + CH NH → NH CH CHO → CH NH + CONH + CH CHO → NH CH CHOH + NH CH CO → NH CH CHOCH OH + NH CH CO → NH CH CHO + H COCH O + NH CH CO → NH CH CHO + H COHCO + NH CH CO → NH CH CHO + COHOCO + NH CH CO → NH CH CHO + CO H + HNCH CHO → NH CH CHOCH OH + HNCH CHO → NH CH CHO + H COCH O + HNCH CHO → NH CH CHO + H COHCO + HNCH CHO → NH CH CHO + COHOCO + HNCH CHO → NH CH CHO + CO NH + CH CHO → HNCH CHOCH CO + OH → CH COOHCH + HOCO → CH COOHH + CH COOH → CH COOHCH OH + CH COOH → CH COOH + H COCH O + CH COOH → CH COOH + H COHCO + CH COOH → CH COOH + COHOCO + CH COOH → CH COOH + CO CH + HOCO → CH COOHCH + CH COOH → C H COOHCH + CH COOH → C H COOHH + C H COOH → C H COOHCH OH + C H COOH → C H COOH + H COCH O + C H COOH → C H COOH + H COHCO + C H COOH → C H COOH + COHOCO + C H COOH → C H COOH + CO HOCO + C H → C H COOH → C H + CO OH + C H CO → C H COOHCH + CH CHO → C H CHOH + C H CHO → C H CHOCH OH + C H CHO → C H CHO + H COCH O + C H CHO → C H CHO + H CO
39 –Table 2—Continued
ReactionHCO + C H CHO → C H CHO + COHOCO + C H CHO → C H CHO + CO CH + CH CHO → C H CHOHCO + C H → C H CHOH + C H CO → C H CHOCH OH + C H CO → C H CHO + H COCH O + C H CO → C H CHO + H COHCO + C H CO → C H CHO + COHOCO + C H CO → C H CHO + CO Note. — Not all reactions involving each species are shown. Equalbranching ratios are assumed, where multiple channels are given. Theformation of the relevant radicals may occur through photodissocia-tion or through hydrogen-abstraction reactions, detailed in Table 3.
40 –Table 3. Activation energy barrier information for important barrier-mediated surface/mantlereactions E A Width Ref.(K) (Å)1 H + CO → HCO — — Andersson (priv. comm.)2 H + H CO → CH OH 4500 1.35 Goumans (priv. comm.)3 H + H CO → CH O 2320 1.35 Goumans (priv. comm.)4 H + H CO → HCO + H OH → CH OH + H OH → CH O + H → CH + H CHO → H + CH CO 2120 1.0 Warnatz (1984)9 H + HCOOCH → H + CH OCO 3970 1.0 Good & Francisco (2002)10 H + HCOOCH → H + HCOOCH → H + COOH 6150 1.0 Evans-Polanyi, CHO → H + NH CO 3500 1.0 Syrstad & Turecek (2001)13 H + CH (OH)CHO → H + CH (OH)CO 2350 1.0 Evans-Polanyi, → NH + CO 2300 1.0 Tsang (1992)15 H + HNCO → NH CO 1390 1.0 Nguyen et al. (1996)16 H + OH → H O + H 2100 1.0 Baulch et al. (1984)17 CH OH + CH CHO → CH OH + CH CO 5300 1.0 Evans-Polanyi18 CH OH + CO → CH (OH)CO 2500 1.0 Garrod et al. (2008)19 CH OH + H CO → CH OH + HCO 2940 1.0 Tsang (1987)20 CH OH + NH CHO → CH OH + NH CO 4320 1.0 Evans-Polanyi21 CH OH + CH (OH)CHO → CH OH + CH (OH)CO 3100 1.0 Evans-Polanyi22 CH OH + HNCO → CH OH + OCN 1200 1.0 Estimate23 CH OH + C H CHO → CH OH + C H CO 3100 1.0 ( OH + C H → CH OH + C H OH + C H → CH OH + C H OH + CH NH → CH OH + H CN 1200 1.0 ( OH + CH NH → CH OH + CH NH OH + CH CN → CH OH + CH CN 6200 1.0 Evans-Polanyi29 CH OH + C H CN → CH OH + C H CN 6100 1.0 Evans-Polanyi30 CH OH + C H CN → CH OH + C H CN 6100 1.0 ( OH + NH CH CN → CH OH + NHCH CN 6100 1.0 ( OH + NH OH → CH OH + HNOH 5130 1.0 Evans-Polanyi33 CH OH + N H → CH OH + NH NH 6100 1.0 ( OH + NH OCH → CH OH + HNOCH OH + NH CH OH → CH OH + HNCH OH 6100 1.0 ( OH + NH CONH → CH OH + NH CONH 6100 1.0 ( OH + NH COOH → CH OH + HNCOOH 6100 1.0 ( OH + CH OCONH → CH OH + CH OCONH 6100 1.0 ( OH + HOCH CONH → CH OH + HOCH CONH 6100 1.0 ( OH + NH COCHO → CH OH + HNCOCHO 6100 1.0 ( OH + CH CONH → CH OH + CH CONH 6100 1.0 ( OH + NH CH COOH → CH OH + HNCH COOH 6100 1.0 ( OH + C H COOH → CH OH + C H COOH 6100 1.0 ( OH + NH C H → CH OH + NH C H OH + NH CH CHO → CH OH + NH CH CO 3100 1.0 (
41 –Table 3—Continued E A Width Ref.(K) (Å)46 CH OH + NH CH CHO → CH OH + HNCH CHO 6100 1.0 ( OH + CH COOH → CH OH + CH COOH 6100 1.0 ( + CH CHO → CH + CH CO 1720 1.0 Evans-Polanyi49 CH + CH OH → CH + CH OH 3600 1.0 Tsang (1987)50 CH + CH OH → CH + CH O 3480 1.0 Tsang (1987)51 CH + CO → CH CO 2500 1.0 Garrod et al. (2008)52 CH + H CO → CH + HCO 4440 1.0 Baulch et al. (1992)53 CH + HCOOCH → CH + CH OCO 5040 1.0 Good & Francisco (2002)54 CH + HCOOCH → CH + HCOOCH + HCOOH → CH + COOH 4550 1.0 Evans-Polanyi56 CH + NH CHO → CH + NH CO 3520 1.0 Boden & Back (1970)57 CH + CH (OH)CHO → CH + CH (OH)CO 1880 1.0 Evans-Polanyi58 CH + HNCO → CH + OCN 1200 1.0 Estimate59 CH O + CH CHO → CH OH + CH CO 1360 1.0 Evans-Polanyi60 CH O + CO → CH OCO 2500 1.0 Garrod et al. (2008)61 CH O + H CO → CH OH + HCO 1500 1.0 Tsang & Hampson (1986)62 CH O + HCOOCH → CH OH + CH OCO 3200 1.0 Evans-Polanyi63 CH O + HCOOCH → CH OH + HCOOCH O + HCOOH → CH OH + COOH 3170 1.0 Evans-Polanyi65 CH O + NH CHO → CH OH + NH CO 1980 1.0 Evans-Polanyi66 CH O + CH (OH)CHO → CH OH + CH (OH)CO 1470 1.0 Evans-Polanyi67 CH O + HNCO → CH OH + OCN 1200 1.0 Estimate68 CH O + C H CHO → CH OH + C H CO 1470 1.0 ( O + C H → CH OH + C H O + C H → CH OH + C H
965 1.0 Evans-Polanyi71 CH O + CH NH → CH OH + H CN 1200 1.0 ( O + CH NH → CH OH + CH NH O + CH CN → CH OH + CH CN 2070 1.0 Evans-Polanyi74 CH O + C H CN → CH OH + C H CN 2000 1.0 Evans-Polanyi75 CH O + C H CN → CH OH + C H CN 2000 1.0 ( O + NH CH CN → CH OH + NHCH CN 2000 1.0 ( O + NH OH → CH OH + HNOH 2000 1.0 ( O + N H → CH OH + NH NH 2000 1.0 ( O + NH OCH → CH OH + HNOCH O + NH CH OH → CH OH + HNCH OH 2000 1.0 ( O + NH CONH → CH OH + NH CONH 2000 1.0 ( O + NH COOH → CH OH + HNCOOH 2000 1.0 ( O + CH OCONH → CH OH + CH OCONH 2000 1.0 ( O + HOCH CONH → CH OH + HOCH CONH 2000 1.0 ( O + NH COCHO → CH OH + HNCOCHO 2000 1.0 ( O + CH CONH → CH OH + CH CONH 2000 1.0 ( O + NH CH COOH → CH OH + HNCH COOH 2000 1.0 ( O + C H COOH → CH OH + C H COOH 2000 1.0 ( O + NH C H → CH OH + NH C H O + NH CH CHO → CH OH + NH CH CO 1470 1.0 (
42 –Table 3—Continued E A Width Ref.(K) (Å)91 CH O + NH CH CHO → CH OH + HNCH CHO 2000 1.0 ( O + CH COOH → CH OH + CH COOH 2000 1.0 ( + CH CHO → NH + CH CO 1250 1.0 Hack et al. (1986)94 NH + CH OH → NH + CH OH 3280 1.0 Evans-Polanyi95 NH + CH OH → NH + CH O 3290 1.0 Evans-Polanyi96 NH + CO → NH CO 2500 1.0 Garrod et al. (2008)97 NH + H CO → NH + HCO 2360 1.0 Evans-Polanyi98 NH + HCOOCH → NH + CH OCO 3360 1.0 Evans-Polanyi99 NH + HCOOCH → NH + HCOOCH + HCOOH → NH + COOH 3340 1.0 Evans-Polanyi101 NH + NH CHO → NH + NH CO 2670 1.0 Evans-Polanyi102 NH + CH (OH)CHO → NH + CH (OH)CO 2400 1.0 Evans-Polanyi103 NH + HNCO → NH + OCN 1200 1.0 Tomeczek & Gradon (2003)104 NH + CH → NH + CH + C H CHO → NH + C H CO 2400 1.0 ( + C H → NH + C H + C H → NH + C H + C H → NH + C H + C H8 → NH + C H + CH NH → NH + H CN 1200 1.0 ( + CH NH → NH + CH NH + CH CN → NH + CH CN 2730 1.0 Evans-Polanyi113 NH + C H CN → NH + C H CN 2690 1.0 Evans-Polanyi114 NH + C H CN → NH + C H CN 2690 1.0 ( + NH CH CN → NH + NHCH CN 2690 1.0 ( + NH OH → NH + HNOH 2690 1.0 ( + N H → NH + NH NH 2690 1.0 ( + NH OCH → NH + HNOCH + NH CH OH → NH + HNCH OH 2690 1.0 ( + NH CONH → NH + NH CONH 2690 1.0 ( + NH COOH → NH + HNCOOH 2690 1.0 ( + CH OCONH → NH + CH OCONH 2690 1.0 ( + HOCH CONH → NH + HOCH CONH 2690 1.0 ( + NH COCHO → NH + HNCOCHO 2690 1.0 ( + CH CONH → NH + CH CONH 2690 1.0 ( + NH CH COOH → NH + HNCH COOH 2690 1.0 ( + C H COOH → NH + C H COOH 2690 1.0 ( + NH C H → NH + NH C H + NH CH CHO → NH + NH CH CO 2400 1.0 ( + NH CH CHO → NH + HNCH CHO 2690 1.0 ( + CH COOH → NH + CH COOH 2690 1.0 ( + C H OH → NH + C H O 4080 1.0 Evans-Polanyi133 O + CO → CO OH → CH OH + H O 359 1.0 Atkinson et al. (2001)135 OH + CH OH → CH O + H O 852 1.0 Warnatz (1984)
43 –Table 3—Continued E A Width Ref.(K) (Å)136 OH + CH CHO → H O + CH CO 600 1.0 Estimate137 OH + CO → CO + H 80 1.0 Ruffle & Herbst (2001)138 OH + CO → COOH 2500 1.0 Garrod et al. (2008)139 OH + HCOOCH → H O + CH OCO 600 1.0 Estimate140 OH + HCOOCH → H O + HCOOCH → H O + COOH 1000 1.0 Estimate142 OH + NH CHO → H O + NH CO 600 1.0 Estimate143 OH + NH CHO → H O + HNCHO 591 1.0 Evans-Polanyi144 OH + CH (OH)CHO → H O + CH (OH)CO 600 1.0 Estimate145 OH + HNCO → H O + OCN 1290 1.0 Tsang (1992)146 OH + CH → H O + CH → H O + NH
925 1.0 Atkinson et al. (2004)148 OH + C H → H O + C H 5280 1.0 Liu et al. (1988)149 OH + C H → H O + C H H CHO → H O + C H CO 600 1.0 Estimate151 OH + C H → H O + C H H → H O + C H
650 1.0 Warnatz (1984)153 OH + C H → H O + C H
730 1.0 Tsang (1991)154 OH + C H8 → H O + C H NH → H O + H CN 591 1.0 ( NH → H O + CH NH CN → H O + CH CN 1030 1.0 Kurylo & Knable (1984)158 OH + C H CN → H O + C H CN 4000 1.0 Evans-Polanyi159 OH + C H CN → H O + C H CN 1000 1.0 Estimate160 OH + C H CN → H O + C H CN 1000 1.0 Estimate161 OH + NH CH CN → H O + NHCH CN 591 1.0 ( OH → H O + HNOH 2140 1.0 Espinosa-Garcia et al. (1993)163 OH + N H → H O + NH NH 591 1.0 ( OCH → H O + HNOCH
591 1.0 ( CH OH → H O + HNCH OH 591 1.0 ( CONH → H O + NH CONH 591 1.0 ( COOH → H O + HNCOOH 591 1.0 ( OCONH → H O + CH OCONH 591 1.0 ( CONH → H O + HOCH CONH 591 1.0 ( COCHO → H O + HNCOCHO 591 1.0 ( CONH → H O + CH CONH 591 1.0 ( CH COOH → H O + HNCH COOH 591 1.0 ( CH COOH → H O + C H COOH 1000 1.0 Estimate174 OH + NH C H → H O + NH C H CH CHO → H O + NH CH CO 600 1.0 ( CH CHO → H O + HNCH CHO 591 1.0 ( COOH → H O + CH COOH 1000 1.0 Estimate178 OH + C H OH → H O + C H O 1510 1.0 Evans-PolanyiNote. — Reactions marked
Evans-Polanyi use the parameters provided by Dean & Bozzelli (1999) unlessotherwise marked with the reference reactions used to fit the Evans-Polanyi relationship. Reactions for whichinsufficient data exist for an Evans-Polanyi are assigned the activation-energy value of the similar reaction indi-
44 – cated. Reactions marked estimate are assigned a generic value appropriate to that reaction type.
45 –Table 4. Binding energies and diffusion barriers used for a selection of important atoms andmolecules, representative of adhesion to an amorphous ice surface.
Species E des E swap E dif H 450 315 158H
430 301 150OH 2850 1995 998H O 5700 3990 1995CH CO 2050 1435 718CH O 2500 1750 875CH OH 5080 3556 1778CH OH 5530 3871 1936CH CO 2200 1540 770CH CO 2325 1628 814CH CHO 2775 1943 971HOCO 5120 3584 1792HCOOH 5570 3899 1950CH OCH H OH 6260 4382 2191HCOOCH (OH)CHO 6680 4676 2338CH COOH 6300 4410 2205(CH O) OCH OH 7580 5306 2653(CH OH) H H COOH 9060 6342 3171C H CHO 5540 3878 1939
46 –Table 4—Continued
Species E des E swap E dif CH CN 4680 3276 1638C H CN 4640 3248 1624C H CN 5540 3878 1939C H CN 7240 5068 2534CH NH NH CHO 5560 3892 1946NH OH 6810 4767 2384(NH ) OCH CH OH 9040 6328 3164NH CH CN 5480 3836 1918NH CH COOH 10100 7070 3535NH C H CH CHO 6610 4627 2314(NH ) CO 7910 5537 2769NH COOH 9080 6356 3178NH COCHO 6710 4697 2349CH OCONH (OH)CONH CONH OCOOH 7620 5334 2667CH (OH)COOH 10200 7140 3570CH OOH 5350 3745 1873CH (OH) ) CO 3500 2450 1225CH OCOCH COCH OH 7410 5187 2594(CH ) CO 6150 4305 2153CH OCOCH OH 8730 6111 3056(CH OH) CO 11300 7910 3955
47 – 48 –Table 5. A selection of gas-phase reactions relevant to glycine included in the chemical network
Reaction RateNH CH COOH + h ν (CR) → NH CH CO + OH 1 . × ζ NH CH COOH + h ν (CR) → CH NH + HOCO 5 . × ζ NH CH COOH + h ν (CR) → CH COOH + NH . × ζ NH CH COOH + h ν (CR) → HNCH COOH + H 1 . × ζ NH CH COOH + h ν → NH CH CO + OH 5 . × - exp( - . × A V ) s - NH CH COOH + h ν → CH NH + HOCO 9 . × - exp( - . × A V ) s - NH CH COOH + h ν → CH COOH + NH . × - exp( - . × A V ) s - NH CH COOH + h ν → HNCH COOH + H 5 . × - exp( - . × A V ) s - C + + NH CH COOH → NH CH COOH + + C 1 . × - cm s - H + + NH CH COOH → NH CH COOH + + H . × - cm s - H O + + NH CH COOH → NH CH COOH + + H O 1 . × - cm s - HCO + + NH CH COOH → NH CH COOH + + CO 1 . × - cm s - He + + NH CH COOH → CH COOH + + NH + He 3 . × - cm s - He + + NH CH COOH → NH CH CO + OH + + He 3 . × - cm s - He + + NH CH COOH → CH NH + + HOCO + He 3 . × - cm s - He + + NH CH COOH → CH COOH + NH + + He 3 . × - cm s - He + + NH CH COOH → NH CH CO + + OH + He 3 . × - cm s - He + + NH CH COOH → CH NH + COOH + + He 3 . × - cm s - NH CH COOH + + e - → NH + CH + CO + H . × - ( T /
300 K) - . cm s - NH CH COOH + + e - → NH + CH + HOCO + H 3 . × - ( T /
300 K) - . cm s - NH CH COOH + + e - → CH NH + CO + OH + H 3 . × - ( T /
300 K) - . cm s - NH CH COOH + + e - → CH NH + CO + H . × - ( T /
300 K) - . cm s - NH CH COOH + + e - → CH NH + HOCO + H 3 . × - ( T /
300 K) - . cm s - NH CH COOH + + e - → CH COOH + NH + H 3 . × - ( T /
300 K) - . cm s - NH CH COOH + + e - → NH CH CO + H O 1 . × - ( T /
300 K) - . cm s - NH CH COOH + + e - → CH NH + HCOOH 1 . × - ( T /
300 K) - . cm s - NH CH COOH + + e - → NH CH COOH + H 1 . × - ( T /
300 K) - . cm s - C + + HNCH COOH → HNCH COOH + + C 1 . × - cm s - H + + HNCH COOH → NH CH COOH + + H . × - cm s - H O + + HNCH COOH → NH CH COOH + + H O 1 . × - cm s - HCO + + HNCH COOH → NH CH COOH + + CO 1 . × - cm s - He + + HNCH COOH → CH NH + COOH + + He 5 . × - cm s - He + + HNCH COOH → CH COOH + NH + + He 5 . × - cm s - He + + HNCH COOH → CH NH + + HOCO + He 5 . × - cm s - He + + HNCH COOH → CH COOH + + NH + He 5 . × - cm s - HNCH COOH + h ν (CR) → CH NH + HOCO 5 . × ζ HNCH COOH + h ν (CR) → CH COOH + NH 1 . × ζ HNCH COOH + h ν → CH NH + HOCO 9 . × - exp( - . × A V ) s - HNCH COOH + h ν → CH COOH + NH 1 . × - exp( - . × A V ) s - H + HNCH COOH → CH NH + HCOOH 1 . × - cm s - CH OH + HNCH COOH → NH CH COOH + H CO 1 . × - cm s - CH O + HNCH COOH → NH CH COOH + H CO 1 . × - cm s - HOCO + HNCH COOH → NH CH COOH + CO . × - cm s - HCO + HNCH COOH → NH CH COOH + CO 1 . × - cm s - NH CH COOH + + e - → NH + CH + CO + H 1 . × - ( T /
300 K) - . cm s - NH CH COOH + + e - → NH + CH + CO + OH 3 . × - ( T /
300 K) - . cm s -
49 –Table 5—Continued
Reaction RateNH CH COOH + + e - → CH NH + CO + H 3 . × - ( T /
300 K) - . cm s - NH CH COOH + + e - → CH NH + CO + OH 3 . × - ( T /
300 K) - . cm s - NH CH COOH + + e - → NH CO + CH + OH 3 . × - ( T /
300 K) - . cm s - NH CH COOH + + e - → CH NH + HOCO 1 . × - ( T /
300 K) - . cm s - NH CH COOH + + e - → CH COOH + NH . × - ( T /
300 K) - . cm s - NH CH COOH + + e - → HNCH COOH + H 1 . × - ( T /
300 K) - . cm s - NH OH + + CH COOH → NH CH COOH + + H O † . × - cm s - NH OH + + CH COOH → NH CH COOH + + H O † . × - / . × - cm s - Note. — The cosmic ray ionization rate, ζ , is set to 1 . × - s - throughout the model. A V denotesvisual extinction. CR denotes cosmic ray induced UV radiation. † These reactions and rates are used only in the models presented in Section 4.
Table 6. Warm-up phase model parameters
Model Time to reach Time to reach200 K 400 KFast 5 × . × Medium 2 × . × Slow 1 × . ×
50 –Table 7. Selection of protostellar ice compositions from the literature, and post-collapse modelvalues, as a percentage of H O Species W33A a NGC 7538 IRS 9 b Sgr A* b Typical Typical Collapse-phaselow-mass c high-mass c model valuesCO 8 16 <
12 29 13 57CO
13 22 14 29 13 18CH CO 6 4 < ≤ ≤ OH 18 5 <
15 13 20–30 5 5 18NH OH – – – – – 0 / 0.55 da Gibb et al. (2000) b See Gibb et al. (2000) for original references c Öberg et al. (2011) d Standard value / value using enhanced NH OH production described in Sec. 4.1
51 –Fig. 1.— Time-dependent fractional abundances of a selection of chemical species, produced bythe fast warm-up timescale model. Solid lines indicate gas-phase species; dotted lines of the samecolor indicate ice-mantle (surface + bulk) abundances of the same species. 52 –Fig. 2.— Time-dependent fractional abundances of a selection of chemical species, produced bythe medium warm-up timescale model. Solid lines indicate gas-phase species; dotted lines of thesame color indicate ice-mantle (surface + bulk) abundances of the same species. 53 –Fig. 3.— Time-dependent fractional abundances of a selection of chemical species, produced bythe slow warm-up timescale model. Solid lines indicate gas-phase species; dotted lines of the samecolor indicate ice-mantle (surface + bulk) abundances of the same species. 54 –Fig. 4.— Time-dependent gas-phase and ice-mantle fractional abundances of hydroxylamine(NH OH), acetic acid (CH COOH) and glycine (NH CH COOH), using the medium warm-uptimescale model with the addition of a fast gas-phase glycine-formation mechanism and a high ini-tial NH OH abundance in the ice mantles, as discussed in Sec. 4.1. Solid lines indicate gas-phasespecies; dotted lines of the same color indicate ice-mantle (surface + bulk) abundances of the samespecies. 55 –Fig. 5.— Simulated emission spectra for the hot-core source NGC 6334 IRS1 at 241.350 – 241.425GHz.
Upper panel : Local, unconvolved emission for the on-source position (i.e. assuming pencilbeam/infinite spatial resolution).
Middle panel : Convolved emission from entire source, assuminga beam width encompassing the strongest glycine-emission region and appropriate to the ALMATelescope (0.4 arcsec).
Lower panel : Convolved emission from entire source, assuming a beamwidth appropriate to the James Clerk Maxwell Telescope ( ∼ r , assuming a pencil beam. Left panel: solid line shows methyl formate emissionat 221.979 GHz (dotted line shows glycine emission of right panel, for direct comparison);
Rightpanel: glycine emission at 218.105 GHz. Line intensity is expressed as brightness temperature.Fig. 7.— Predicted molecular line-strength maps for lines of sight toward NGC 6334 IRS 1,assuming a pencil beam (i.e. unconvolved).
Left panel: methyl formate emission at 221.979GHz;
Right panel: glycine emission at 218.105 GHz. Line intensity is expressed as brightnesstemperature; temperature scales are different in each panel. 57 –Table 8. Peak fractional abundances and corresponding temperatures for a selection ofmolecules, for each warm-up model
Fast Medium SlowMolecule n [ i ] / n H T n [ i ] / n H T n [ i ] / n H T(K) (K) (K)H O 1.6e-4 392 1.6e-4 395 1.6e-4 398CO 9.5e-5 400 1.0e-4 391 1.2e-4 398CO + CO 4.6e-6 43 3.7e-6 42 5.5e-7 39CH OH 1.1e-5 123 9.1e-6 122 3.8e-6 121NH O H 1.4e-9 27 1.9e-9 26 2.5e-9 26C H H H H H CN 2.1e-10 65 1.6e-11 47 1.1e-11 27CH CN 4.9e-9 400 2.1e-9 92 1.3e-9 90C H CN 1.1e-8 108 5.6e-9 398 5.6e-9 202C H CN 5.7e-9 123 7.7e-8 122 3.0e-8 122C H CN 6.0e-9 153 1.0e-8 149 8.4e-10 144CH CO 9.0e-8 78 1.9e-8 77 1.1e-8 203CH CHO 3.1e-9 400 9.4e-9 337 1.4e-8 154C H CHO 6.9e-9 123 1.2e-8 120 2.6e-8 116CH NH 1.1e-8 400 2.4e-8 398 1.5e-8 161CH NH CHO 3.9e-7 123 1.5e-7 122 2.9e-9 117NH CN 2.3e-8 267 3.6e-8 205 3.3e-8 195NH OH 1.6e-10 145 6.0e-10 141 1.7e-9 135C H OH 5.9e-8 135 5.8e-8 131 4.9e-8 127CH OCH
58 –Table 8—Continued
Fast Medium SlowMolecule n [ i ] / n H T n [ i ] / n H T n [ i ] / n H T(K) (K) (K)HCOOCH H COOH 1.0e-10 134 5.0e-10 131 7.2e-9 130C H COOH 1.1e-9 195 2.7e-10 190 3.3e-9 183CH COCHO 3.4e-8 81 3.0e-8 76 3.5e-9 74(CH ) CO 1.5e-9 72 1.0e-8 68 1.9e-9 66CH CONH OCOCH (OH)COCH COCHO 6.6e-8 145 2.6e-8 141 3.4e-8 136NH COOH 1.8e-10 193 1.2e-9 188 9.8e-10 182(NH ) CO 7.1e-8 169 1.2e-7 163 3.2e-8 157NH CH CHO 7.5e-9 141 1.2e-8 136 2.9e-9 134NH CH CN 4.3e-9 123 1.2e-8 122 4.7e-9 118NH CH COOH 8.4e-11 216 4.6e-10 207 8.1e-9 203NH C H ) ONH (OH)NH OCOCHO 4.5e-11 118 5.1e-13 128 1.6e-12 105CH OCOOH 1.5e-12 164 3.8e-12 160 1.2e-15 151CH OCONH O) CO 3.4e-12 137 3.4e-12 135 1.8e-13 127CH OCOCH OH 1.8e-9 187 4.3e-10 180 1.0e-14 125CH OOH 7.7e-13 123 3.9e-13 120 9.2e-14 112(CH O) OCH OH 1.5e-8 166 1.4e-9 160 1.1e-13 151CH (OH)CHO 2.9e-7 143 1.1e-7 141 1.9e-8 147CH (OH)COCHO 3.3e-8 240 5.0e-8 209 1.1e-8 195CH (OH)COOH 4.5e-10 216 6.6e-11 202 4.1e-15 134CH (OH)CONH OH) CO 4.8e-9 222 2.2e-10 203 5.8e-13 191CH (OH) OH)
59 –Table 9. Simulated line intensities toward NGC 6334 IRS1, for a selection of molecules andbeamwidths, using fast warm-up timescale model.
Molecule Line E upper Peak simulated Beam Convolved Convolved Observedfrequency local intensity width intensity integrated intensity integrated intensity a (GHz) (K) (K) (arcsec) (K) (K km s - ) (K km s - )Methanol 220.079 96.61 113 21.9 b OH) 230.027 39.83 118 21.0 b b b b b b b ) 221.979 154.7 248 21.7 b b b b b b b b CH COOH) 11.4 c d d b c d d b c d d b c d d b c d d b c d d
60 – a Observations by Bisschop et al. (2007) b Appropriate to JCMT (12 m) observations at this frequency c Appropriate to IRAM 30 m observations at this frequency d Approximate value, within ALMA capabilities at this frequency
61 –Table 10. Simulated line intensities toward NGC 6334 IRS1, for a selection of molecules andbeamwidths, using medium warm-up timescale model.
Molecule Line E upper Peak simulated Beam Convolved Convolved Observedfrequency local intensity width intensity integrated intensity integrated intensity a (GHz) (K) (K) (arcsec) (K) (K km s - ) (K km s - )Methanol 220.079 96.61 112 21.9 b OH) 230.027 39.83 118 21.0 b b b b b b b ) 221.979 154.7 166 21.7 b b b b b b b b CH COOH) 11.4 c d d b c d d b c d d b c d d b c d d b c d d
62 – a Observations by Bisschop et al. (2007) b Appropriate to JCMT (12 m) observations at this frequency c Appropriate to IRAM 30 m observations at this frequency d Approximate value, within ALMA capabilities at this frequency
63 –Table 11. Simulated line intensities toward NGC 6334 IRS1, for a selection of molecules andbeamwidths, using slow warm-up timescale model.
Molecule Line E upper Peak simulated Beam Convolved Convolved Observedfrequency local intensity width intensity integrated intensity integrated intensity a (GHz) (K) (K) (arcsec) (K) (K km s - ) (K km s - )Methanol 220.079 96.61 117 21.9 b OH) 230.027 39.83 127 21.0 b b b b b b b ) 221.979 154.7 0.792 21.7 b b b b b b b b CH COOH) 11.4 c d d b c d d b c d d b c d d b c d d b c d d
64 – a Observations by Bisschop et al. (2007) b Appropriate to JCMT (12 m) observations at this frequency c Appropriate to IRAM 30 m observations at this frequency d Approximate value, within ALMA capabilities at this frequency
65 –
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Molecule Line E upper Peak simulated Beam Convolved Convolvedfrequency local intensity width a intensity integrated intensity(GHz) (K) (K) (arcsec) (K) (K km s - )Hydroxylamine 151.102 46.33 0.0354 41.5 4.37e-5 4.20e-4(NH OH) 151.118 14.51 0.0391 41.5 5.01e-5 4.81e-4164.341 116.7 8.05e-4 38.2 1.08e-6 1.03e-5164.627 94.92 8.10e-4 38.1 1.12e-6 1.07e-5164.883 75.60 7.93e-4 38.0 1.13e-6 1.08e-5Note. — * Line data and partition function obtained from the Cologne Database for Molecular Spec-troscopy (CDMS). a Appropriate to NRAO 12 m observations at this frequency.
Table 13. Simulated line intensities for hydroxylamine (NH OH) toward W3 IRS5, using medium warm-up model with the gas-phase glycine-formation mechanism and high initialNH OH ice-mantle abundance discussed in Sec. 4.1.
Molecule Line E upper Peak simulated Beam Convolved Convolvedfrequency local intensity width a intensity integrated intensity(GHz) (K) (K) (arcsec) (K) (K km s - )Hydroxylamine 151.102 46.33 34.7 41.5 0.0424 0.407(NH OH) 151.118 14.51 37.7 41.5 0.0494 0.475164.341 116.7 0.883 38.2 0.00111 0.0107164.627 94.92 0.885 38.1 0.00115 0.0111164.883 75.60 0.865 38.0 0.00117 0.0112Note. — * Line data and partition function obtained from the Cologne Database for Molecular Spec-troscopy (CDMS). a Appropriate to NRAO 12 m observations at this frequency.
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