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Chemical effects on ices: studies with a chemo-dynamical model

Jeong-Eun Lee Kyung Hee University University of Texas at Austin. Chemical effects on ices: studies with a chemo-dynamical model. Contents:. Very Low Luminosity Objects ( VeLLOs , L<0.1 L  ) Episodic accretion & Chemistry (Lee 2007) CO 2 ice in Low Luminosity Objects (L<1 L  )

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Chemical effects on ices: studies with a chemo-dynamical model

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  1. Jeong-Eun Lee Kyung Hee University University of Texas at Austin Chemical effects on ices:studies with a chemo-dynamical model

  2. Contents: Very Low Luminosity Objects (VeLLOs, L<0.1L) • Episodic accretion & Chemistry (Lee 2007) CO2 ice in Low Luminosity Objects (L<1L) • Kim et al. (2012) • Lee et al. (2004) -chemo-dynamical model • Dunham et al. (2010) -luminosity model of episodic accretion Other ices • Surface chemistry with the model of Lee (2007)

  3. VeLLOs • Protostars in the quiescent phase or Proto-brown dwarfs? • If VeLLOs had a constant low accretion rate through their evolution, chemistry must be similar to that of starless cores • Depletion of CO, centrally peaked N2H+, high level of deuteration • If VeLLOs are in their quiescent phase after accretion bursts, they will be different from either Class 0/I or starless cores in chemical distributions (Lee 2007, Visser & Bergin 2012) • Therefore, chemistry can be used as a fingerprint of episodic accretion. • A possible example of episodic accretion – IRAM 04191

  4. IRAM 04191 L~0.08L 3.6 4.5 8.0 Strong Outflow (Bellocheet al. 2002) PdBI + IRAM 30 m N2H+ depletion at the continuum peak (Belloche& Andre 2004)

  5. Chemo-Dynamical Model Evolution Model of Luminosity Lee, et al (2004)

  6. Chemical evolution in episodic accretion (Lee 2007) • Chemical distributions for IRAM0419 • assumptions: • constant infall from envelope to disk • episodic accretion from disk to star • (accretion event every 104 yrs for 103 yrs)‏ • Model prameters: • Mcore = 1 M • Rcore = 6200 AU • normal accretion rate = 4.8 x 10-6 M/yr • accretion rate (accretion phase) = 10 x normal rate • accretion rate (quiet phase) = 0.01 x normal rate Young and Evans (2004)

  7. Difference between standard and episodic accretion models Episodic Accretion Continuous Accretion CO and N2H+ abundances

  8. Expectation from ALMA Episodic Accretion Continuous Accretion Cycle 2 ALMA targets Band6 C34-1 Θ=2” Simulation of observations in C18O J=2-1

  9. Constrain the time scale after a outburst ice gas time After burst

  10. Caveat; No consideration of surface chemistry

  11. Problem in C18O and N2H+ Standard and Episodic accretion models with the chemical network without surface chemistry cannot explain the observed luminosity or strength of C18O and N2H+ toward CB130-1. Observation Model • Continuous accretion model cannot match the source luminosity. Lint_mod = 0.01 L⊙< Lint_obs = 0.15 L⊙ • Episodic accretion model has too strong C18O and too weak N2H+. Kim et al., 2011

  12. A possible solution; part of CO gas gets converted to CO2 ice when it is frozen on to grain surfaces. CO2 is a useful constraint for episodic accretion because of its distinct pure ice feature.

  13. Pure CO2 Ice Formation Distillation CO CO2 CO CO2 CO CO DUST DUST CO2 T > 20 K CO2 CO2 CO CO2 Segregation CO CO2 H2O CO2 H2O T > 50 K CO2 DUST H2O CO2 H2O DUST CO2 H2O • Formation of pure CO2 ice requires at least 20 K. • Pure CO2 ice formation is an irreversible process. H2O CO2 H2O H2O

  14. Laboratory Data Laboratory data from Leiden Observatory data base. Pure CO2 ice • CO2:H2O mixture, CO:CO2 mixture (Ehrenfreund et al. 1997) • Only the pure CO2 ice (van Broekhuizen et al. 2006) component has double peak.

  15. Dust Temperature is Too Low CO evaporation temperature Dust Temperature (K) Radius (AU) • The envelope around low luminosity protostars with 0.6 L does NOT have a dust temperature higher than 20 K to form the pure CO2 ice. • If we can detect the pure CO2 ice feature around low luminosity protostars, then it can be an evidence of the past high accretion rate!

  16. Observation • CO2 ice with Spitzer/IRS SH mode (R=600) • 19 low luminosity protostars with Lint < 0.7 L • (PI: M. Dunham) • 18 of them have Lint < 0.6 L. • 3 of them have Lint < 0.1 L. • 50 higher luminosity protostars with Lint > 1 L • (c2d:Pontoppidan et al. 2008) • C18O (J = 21; 219.560352 GHz) toward 11 low luminosity protostars at CSO. Kim et al., 2012

  17. Pure CO2 Ice Detections at Low Luminosity Protostars CB130-1 0.15 L⊙ • Six low luminosity embedded protostars show significant double peaks caused by the pure CO2 ice. • Three more sources show evidence of pure CO2 ice. • Column Density is calculated 0.54 L⊙ CB68 SSTc2d J032845.3 +310542.0 0.26 L⊙ SSTc2d J032923.5 +313329.5 0.20 L⊙ SSTc2d J125342.9-771511.5 0.14 L⊙

  18. Component Analysis with Laboratory Data CO-CO2 mixture IRAM 04191+1522 Water-rich CO2 ice Pure CO2 ice Total CO2 ice Double peak comes from the pure CO2 ice component Internal luminosity of IRAM 04191+1522 is 0.08 L⊙, but it has the pure CO2 ice component. The source hadhigher temperatures than the dust temperature derived from the current SED.

  19. Tests with Chemo-dynamical Models • Chemo-dynamical models • Continuous accretion + chemical network • without surfacechemistry • Continuous accretion + CO to CO2 ice conversion • Episodic accretion + chemical network • without surface chemistry • Episodic accretion + CO to CO2 ice conversion Kim et al., 2012

  20. Result: C18O gas Kim et al., 2012

  21. Result: CO2 ice Best Fit Kim et al., 2012

  22. Caveat; No explicit surface chemistry • Inclusion of surface chemistry explicitly using rate equations • Willacy et al. (2006), Garrod and Herbst (2006), Dodson-Robinson et al. (2009), Yu et al. (in prep.)

  23. ad hoc approximation vs. explicit surface chemistry ad hoc approximation Explicit surface chemistry Branching ratio between CO ice and CO2 ice = 0.5 : 0.5 CO + grain gCO (50%) or gCO2 (50%)

  24. CO CO AKARI spectrum of a low luminosity source • CO2 • CO2 • H2O • H2O J034351.02+320307.9 (L=0.33 L, Dunham et al. 2008)

  25. ICES • Continuous accretion • Episodic accretion

  26. Further constraints forepisodic accretion • ALMA observations for the distribution of gaseous molecules • Other ices observed with Spitzer/IRS and AKARI • e.g. Boogert et al. (2011) • e.g. Noble et al. (2013), Lee et al. (in prep.)

  27. Summary • Episodic Accretion Model can explain • presence of pure CO2 ice in low luminosity protostars • low luminosity itself, strength of molecular lines, and total CO2 ice column densitywith the ad hoc ice conversion of CO to CO2 • Surface chemistry must be included more explicitly. • Chemo-Dynamical model for the episodic accretion model could be constrained better by existing IR ice spectra and future ALMA observations.

  28. Thank you.

  29. Boogertet al., 2011

  30. Episodic accretion modelwith/without surface chemistry No surface chemistry With surface chemistry CO and N2H+ abundances

  31. GO + GCO  GCO2 • GO + GHCO  GCO2 + GH • GOH + GCO  GCO2 + GH • Assume ONLY GH, GC, GN, GO, GS, GH2, GCH, GOH, and GNH are mobile.

  32. Grain surface reaction

  33. For exothermic reaction • without an activation energy : P =1 • With an activation energy (Ea) b = 1 Å , μr = reduced mass

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