Pith. sign in

REVIEW 4 major objections 5 minor 2 cited by

Near- to mid-infrared spectroscopic study of ice analysis using the AKARI/IRC and Spitzer/IRS spectra

T0 review · 4 major / 5 minor · reviewed 2026-08-15 · deepseek-v4-flash

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗ Review JSON

Pith's one-line read The paper derives consistent water-ice column densities from the 3.05 and 13.6 µm bands and finds that CO ice abundance drops as protostars evolve from Class 0 to Class I.

desk verdict A competent, incremental ice-fitting study of four protostars with genuinely new combined spectra, undermined mainly by an overclaimed evolutionary trend that the authors' own text disowns. read the letter →

arxiv 2505.05390 v1 pith:TZCGYAIL submitted 2025-05-08 astro-ph.SR astro-ph.GA

Jaeyeong Kim , Jeong-Eun Lee , Chul-Hwan Kim , Woong-Seob Jeong , Yao-Lun Yang This is my paper · ORCID
classification astro-ph.SRastro-ph.GA
keywords astrochemistryinterstellariceslow-massprotostarsinfraredspectroscopyAKARIIRCSpitzerIRSicecolumndensityCOsublimation
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

This paper combines 2.5–5 µm AKARI spectra with 5–30 µm Spitzer spectra of four low-mass protostars at different evolutionary stages and fits the full infrared absorption with laboratory ice profiles to derive, for the first time, H$_2$O ice column densities from the 3.05 µm stretching mode and the 13.6 µm libration mode simultaneously. The authors use the same global fit to separate blended absorptions of CO$_2$, CO, NH$_3$, CH$_3$OH, and candidate organic ices, producing complete ice inventories for Per-emb 25, Ced 110 IRS4, B1 a, and RNO 91. Their central astrophysical result is that CO ice abundance declines from Class 0 to Class I, which they attribute to sublimation as the protostar heats its envelope. The work matters because ice mantles are the raw material for planet formation and because the same decomposition method is directly applicable to JWST spectra, where higher resolution can resolve what remains unattributed here.

What carries the argument

The load-bearing device is the global spectral decomposition: laboratory ice absorbance profiles, taken from published measurements at fixed temperatures and mixture ratios, are convolved to the telescope resolution and summed to reproduce the observed optical-depth spectrum; each component's column density then follows from the band-strength relation $N = (1/A)\int \tau\,d\nu$, where $A$ is the laboratory band strength. The key named ingredients are the water-rich mixture H$_2$O:CO:NH$_3$:CO$_2$:CH$_3$OH = 100:20:20:14:10 at 10 K, the CO:CO$_2$ = 100:70 and CH$_3$OH:CO$_2$ = 1:2 mixtures used for the CO$_2$ bending feature, and a silicate-subtraction step that couples the GCS 3 silicate template with synthetic amorphous olivine and pyroxene profiles. This machinery lets the authors attribute each absorption band to an intrinsic ice carrier and converts the fitted profiles into the column densities of Tables 3 and 4. The H$_2$O libration mode (10–20 µm) serves as the anchor because it is less blended than the stretch and bend modes, and the agreement between stretch- and libration-derived columns is what validates the whole decomposition.

What would settle it

A JWST spectrum of one of these sources that resolves both water bands without saturation, combined with a laboratory band-strength measurement of the water-rich mixture at 10–20 K, would settle whether the simultaneous H$_2$O column densities and the derived abundances are correct.

Watch

Extended reading notes

Core claim

On its own terms, the paper establishes a reliable decomposition of the 2.5–30 µm ice absorption toward four low-mass protostars. After removing the continuum and the 9.7 and 18 µm silicate bands, using both a template and synthetic amorphous olivine and pyroxene profiles, the authors fit all remaining absorption with laboratory ice absorbance data convolved to each instrument's resolution. The fit includes H$_2$O-rich mixtures (H$_2$O:CO:NH$_3$:CO$_2$:CH$_3$OH = 100:20:20:14:10 at 10 K), CO- and CH$_3$OH-mixed CO$_2$ ices, pure CO$_2$, pure and mixed CO with warm gas CO, and pure NH$_3$, CH$_3$OH, HCOOH, CH$_3$CHO, CH$_3$CH$_2$OH, and NH$_4^+$ profiles. The simultaneous derivation of the H$_2$O column from the 3.05 µm stretch and 13.6 µm libration modes yields values that agree within uncertainties, justifying the use of the libration mode as the abundance reference. The same fit gives CO$_2$ to H$_2$O ratios near 0.3 in all sources and a CO to H$_2$O ratio that decreases from 0.23 in the Class 0 source to 0.10–0.14 in the Class I sources. Toward RNO 91, a resolved double-peaked 15.2 µm CO$_2$ feature is interpreted as pure CO$_2$ ice left behind after thermal evaporation of CO, making it a possible infrared tracer of recent accretion bursts.

Load-bearing premise

The whole analysis rests on the assumption that the real ice mantles are exactly described by the laboratory mixture profiles and band strengths chosen here, with fixed ratios such as H$_2$O:CO:NH$_3$:CO$_2$:CH$_3$OH = 100:20:20:14:10 at 10 K that the paper never varies; if the true ice composition, temperature, or morphology differs, every derived column density and abundance in Tables 3 and 4 shifts, and the paper's own 6–8 µm residual shows the decomposition is not closed.

Editorial extensions

If this is right

  • The combined 2.5–30 µm analysis yields new ice inventories for Per-emb 25, Ced 110 IRS4, B1 a, and RNO 91, with column densities and abundances listed in Tables 3 and 4.
  • The agreement between the H$_2$O stretch- and libration-mode columns supports using the 13.6 µm libration band as the abundance reference, avoiding contamination by 3 µm absorptions from NH$_3$ and CH$_3$OH.
  • The decrease in CO ice abundance from the Class 0 source to the Class I sources supports the scenario in which protostellar heating sublimates CO ice into the gas phase as the system evolves.
  • The resolved double-peaked 15.2 µm CO$_2$ feature toward RNO 91 indicates pure CO$_2$ ice left after thermal processing, a potential infrared tracer of episodic accretion and recent accretion bursts.
  • The silicate-subtraction and global-fitting method applies directly to JWST ice spectra, where higher spectral resolution can address the absorption that remains unattributed in the 6–8 µm range.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • If the same stretch-versus-libration water check were run on a large JWST sample, systematic differences between the two bands would quantify how much NH$_3$ and CH$_3$OH contamination actually hides inside the 3 µm water band.
  • Because the decomposition fixes the mixture ratios without testing alternatives, the abundances in Tables 3 and 4 should be read as conditional on those laboratory recipes; new band-strength measurements for realistic multi-component ices could re-scale all of them.
  • The pure CO$_2$ signature in RNO 91 predicts that other protostars with known recent accretion bursts should also show the double-peaked 15.2 µm feature, while quiescent low-mass protostars should not.
  • The unattributed 6–8 µm residual suggests the ice inventory is not closed; high-resolution MIRI spectra of the same targets could identify additional carriers such as CH$_4$ or NH$_4^+$ in that region.
Share X Bluesky LinkedIn Reddit HN

Signed reviews

No signed human review yet.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

4 major / 5 minor

Summary. The paper presents combined 2.5–30 μm AKARI/IRC and Spitzer/IRS spectra of four low-mass protostars (Per-emb 25, Ced 110 IRS4, B1 a, and RNO 91) and analyzes the ice absorption features by fitting experimental laboratory profiles. The authors determine continua, subtract silicate absorption using a GCS 3 template and a synthetic amorphous olivine/pyroxene profile, and then globally fit ice components including H2O (stretch, bend, and libration), CO2, CO, NH3, CH3OH, HCOOH, CH3CHO, CH4, and NH4+. They derive column densities and report ice abundances relative to H2O (calculated from the libration mode), compare with previous AKARI and Spitzer results, identify a tentative decrease in CO ice abundance from Class 0 to Class I, and suggest that pure CO2 in RNO 91 traces a past accretion burst. The paper also states the method can be applied to JWST ice spectra.

Significance. If the derived column densities are accurate, this work provides new ice inventories for four protostars, including the first simultaneous use of the H2O stretch and libration modes in this sample and an analysis of the CO2 bending mode rather than the unresolved AKARI stretching mode. The comparison with dense-cloud JWST observations is useful, and the identification of pure CO2 in RNO91 is a concrete, potentially interesting result. The authors are also honest about several known limitations, such as the RNO91 stretch-mode mismatch and the unattributed 6–8 μm residual. However, the central evolutionary claim (CO ice decreasing from Class 0 to I) is not supported by the four-source sample and the quoted statistical-only uncertainties, and the fixed laboratory mixture ratios used in the decomposition are never tested. The paper's strengths are the careful data combination and a transparent fitting approach, but the overreach in the abstract and summary requires revision.

major comments (4)
  1. [§5, Table 4, Abstract, §6] Section 5 states that "It is insufficient to reveal clear trends linked to the differences in ice abundances across only the four samples and the evolutionary stages of protostars," yet the Abstract and Section 6 repeat the CO ice abundance decrease as a finding. With only four sources, and with Ced 110 IRS4 (Class 0/I) at X(CO)=0.18±0.04 overlapping B1-a (0.10±0.01) and RNO 91 (0.14±0.06) within 2σ, the ordering is not statistically robust. Please either remove the trend claim from the Abstract/Summary or support it with a quantitative significance test (e.g., bootstrap or weighted regression) that includes systematic uncertainties.
  2. [§4.2, Table 2, Eq. (1)] The CO ice decomposition at 4.67 μm uses fixed laboratory mixture ratios (H2O-rich 100:20:20:14:10, CO:CO2=100:70, CO:CH3OH=1:1; Table 2) that are never varied, although Eq. (1) uses mixture-specific band strengths. Different published protostellar ice mixtures would redistribute N(CO) among components and change the total. The authors should test the sensitivity by refitting with alternative mixtures (e.g., those in Boogert et al. 2015 or Rocha et al. 2025) and report the range of resulting CO abundances, since this is load-bearing for the claimed evolutionary trend.
  3. [§3.1, Table 3] The uncertainties in Table 3 are explicitly based only on statistical errors in the spectra. The H2O libration-mode column densities, which are the denominators for all abundances in Table 4, depend on the silicate-template scaling and the 18–30 μm continuum anchoring described in Section 3.1, and these systematic errors are not propagated. The authors should quantify the continuum/silicate systematic uncertainty (e.g., by varying the silicate template, the fitting ranges, and the AKARI-to-Spitzer scaling) and add it in quadrature to the reported values, or at least provide a quantitative estimate of its magnitude.
  4. [§4.2] The paper reports that "a significant fraction of the 6−8 μm absorption remains unattributed," so the fitted model does not fully describe the spectra. This incomplete modeling can bias the scaling of other components, particularly CH3OH and NH4+, and its potential effect on the derived column densities should be discussed or bounded. Even if the 6–8 μm residual does not directly affect the CO measurement at 4.67 μm, it indicates that the global fit is not closed, which should be acknowledged as a systematic limitation in the abundance analysis.
minor comments (5)
  1. [Throughout text and figure captions] The manuscript contains many corrupted character sequences (e.g., lines of "/uni00000015/uni00000011/..." after the references and in Figures 1–9 captions). These must be cleaned before publication, as they currently appear as broken glyph placeholders.
  2. [§3.1] "six-order polynomial" should be "sixth-order polynomial," and "third-to-fourth-order" should be "third- to fourth-order."
  3. [§2.1] "We summarized their positions" should be "We summarize their positions" for consistency with the present-tense style used elsewhere.
  4. [§3.1, Figure 2 caption] The phrase "The fitted laboratory profiles well cover the broad 13 μm absorption" is awkward; consider "The fitted laboratory profiles cover the broad 13 μm absorption well."
  5. [Table 4 caption] The table lists comparison values with footnote markers (e.g., "0.19b−0.42c") but the footnote letters are not explained in the caption; please specify which references each marker corresponds to.

Circularity Check

0 steps flagged · score 1.0 of 10

No significant circularity: ice column densities are derived by fitting external laboratory absorbance profiles to observed spectra via Eq. (1), and the CO ice evolutionary trend is an interpretation of those fitted values, not an input to the fit.

full rationale

The paper's central derivation is a spectral decomposition: observed optical depth spectra are fitted with experimental ice absorbance profiles (Gerakines et al. 1995; Ehrenfreund et al. 1996; Fraser & van Dishoeck 2004), and column densities are computed as N = integral(tau dnu)/A in Eq. (1). The laboratory band strengths and profile shapes are independent external inputs, not outputs of this paper, and the observed spectra are independent of the derived abundances. The H2O libration-mode column density used as the abundance denominator comes from a separate vibrational mode than the stretch-mode check, and the CO column density comes from the 4.67 micron stretching mode, so the reported X(CO) = N(CO)/N(H2O) is not self-defined. The only self-citations (Kim et al. 2022) concern data reduction and the spectral-convolution methodology for AKARI IRC spectra; they carry method, not the conclusion. The paper also explicitly concedes the statistical limitation of its evolutionary claim: 'It is insufficient to reveal clear trends linked to the differences in ice abundances across only the four samples and the evolutionary stages of protostars.' That caveat concerns sample size and systematic assumptions, not circularity. The fixed laboratory mixture ratios in Table 2 are untested assumptions that could shift the derived values, but a dependence on external inputs is not the same as the derivation reducing to its own conclusion by construction. No self-definitional step, fitted-input-called-prediction step, or load-bearing self-citation chain is present.

Assumptions & free parameters 6 free parameters · 6 assumptions · 0 invented entities

The central claim rests on external laboratory data and adopted template and mixture choices rather than new theory. The main non-negotiable inputs are the silicate subtraction recipe, the fixed laboratory mixture ratios and band strengths, and the assumption that the H2O libration band is an unbiased abundance reference. These are standard in the field, but none are independently verified here.

free parameters (6)
  • Per-target continuum polynomial coefficients = not reported
    AKARI spectra are fitted with third-to-fourth-order polynomials and Spitzer mid-IR with a sixth-order polynomial over manually selected continuum windows (Sec 3.1, Fig 2a).
  • Silicate template scaling factor = not reported
    The GCS3 or synthetic olivine and pyroxene absorption profile is scaled to match the 9.7 and 18 micron silicate absorption for each source before ice fitting (Sec 3.1).
  • Ice component scale factors = reported as column densities in Table 3
    Each laboratory ice absorbance profile is scaled to the observed optical depth in a global fit; integrated optical depth divided by band strength gives column density (Eq 1, Sec 4.3).
  • AKARI to Spitzer flux scaling = not reported
    AKARI spectra are scaled to match the short-wavelength end of the Spitzer spectra; for RNO91 a short-exposure spectrum was scaled up using long-exposure data (Sec 3.1).
  • Amorphous and crystalline H2O ice mixing fraction = not reported
    Pure 15 K amorphous and 160 K crystalline H2O profiles are combined to fit the 3.05 and 13.6 micron features; the relative fraction is a fit output (Sec 3.1, 4.1).
  • Warm CO gas temperature and column = 50 to 90 K
    Gaseous CO absorption profiles in the 50 to 90 K range are included to fit the broad 4.67 micron wing (Sec 4.2).
assumptions (6)
  • domain assumption Laboratory ice spectra from Gerakines et al. 1995, Ehrenfreund et al. 1996, and Fraser and van Dishoeck 2004 represent interstellar ice absorption at the relevant temperatures and compositions.
    The entire decomposition scales these laboratory profiles to the observed optical depth (Sec 4, Table 2).
  • domain assumption Adopted ice mixture ratios, including H2O:CO:NH3:CO2:CH3OH = 100:20:20:14:10, CO:CO2 = 100:70, CH3OH:CO2 = 1:2, and CO:CH3OH = 1:1, are correct for these envelopes.
    These ratios are fixed in advance from prior literature, and no sensitivity analysis is performed (Sec 4.1, 4.2).
  • domain assumption Silicate absorption is well described by the GCS3 template or a synthetic amorphous olivine and pyroxene mixture computed with optool for a grain size distribution of a^-3.5, grain sizes 0.1 to 1 micron, and 87 percent silicate and 13 percent carbon dust.
    Subtracting this template defines the ice optical depth scale in the 8 to 22 micron range (Sec 3.1).
  • domain assumption Band strengths A listed in Table 2 are accurate for the adopted ice phases.
    Column density uses N = integral(tau dnu) / A (Eq 1); any error in A scales all abundances.
  • domain assumption The H2O libration mode near 13.6 micron is cleanly separable from silicate and other ice absorption.
    It is used as the abundance reference for all other species (Sec 4.3, Table 4).
  • domain assumption Convolving laboratory spectra with the instrument resolution adequately captures the observed band shapes.
    The fitting procedure assumes the convolved lab profiles reproduce the observed optical depth features across the full 2.5 to 22 micron range (Sec 4).

how reviews work

0 comments
Cite this review

Pith. "Pith review of Near- to mid-infrared spectroscopic study of ice analysis using the AKARI/IRC and Spitzer/IRS spectra." pith.science (2026). https://pith.science/paper/TZCGYAIL

@misc{pith2026250505390,
  author       = {Pith},
  title        = {Pith review of: Near- to mid-infrared spectroscopic study of ice analysis using the AKARI/IRC and Spitzer/IRS spectra},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/TZCGYAIL}},
  note         = {Machine review of arXiv:2505.05390}
}
abstract

We present the combined 2.5$-$30$\mu$m spectra of four protostars acquired with the infrared camera and the infrared spectrograph on board the AKARI and Spitzer space telescopes, respectively. To analyze the ice absorption features in the 8$-$22$\mu$m, we first performed a continuum determination process on mid-infrared spectra and applied a method to subtract the silicate absorption. We conducted a global fitting process to the absorption features in the combined infrared spectra using the experimental ice absorbance data to identify the intrinsic absorption of each ice component. We first derived the H$_{2}$O ice column densities of both stretch and libration modes at 3.05$\mu$m and 13.6$\mu$m simultaneously. We also identified the absorption features containing NH$_{3}$, CH$_{3}$OH, CO$_{2}$, and CO and decomposed their mixed components and compared their ice abundances at different evolutionary stages of the protostars. We explored possible absorptions of the organic ice species such as HCOOH, CH$_{3}$CHO, and CH$_{3}$CH$_{2}$OH in the mid-infrared ranges. The ice analysis method developed in this study can be applied to the ice spectra obtained by the James Webb Space Telescope.

Figures

Figures reproduced from arXiv: 2505.05390 by the authors.

Figure 1
Figure 1. The observed AKARI IRC spectra (left) and Spitzer IRS spectra (right) for all the sources in this study. In the case of RNO 91, we used the IRC spectrum reduced with short-exposure data to avoid the flux saturation of the target. The Spitzer spectra are plotted in log scale while the AKARI spectra are plotted in linear scale. Kim et al. 12 [PITH_FULL_IMAGE:figures/full_fig_p012_1.png] view at source ↗
Figure 2
Figure 2. An example of the continuum determination process for Per-emb 25. Panel (a) presents the initial continuum fit to the target spectrum using a six-order polynomial (green dashed line) with the selected wavelengths marked by red points. In Panel (b), the GCS 3 template spectrum (brown dotted line) is overlaid onto the fitted continuum to examine the absorption of silicate features to the target spectrum. Panel (c) sho… view at source ↗
Figure 3
Figure 3. Combined infrared spectra from the AKARI IRC and Spitzer IRS observations for all the sources in this study. The thick green dashed line shows the continuum determined by third- to fourth-order polynomial fitting of the AKARI spectrum. Since the flux levels of the AKARI and Spitzer spectra are not identical, we scaled the AKARI spectrum to match the flux level of the short-wavelength end of the Spitzer spectrum. The… view at source ↗
Figures from the paper (6 more)
Figure 4
Figure 4. Figure 4: Same spectra as [PITH_FULL_IMAGE:figures/full_fig_p015_4.png]
Figure 5
Figure 5. Figure 5: Same spectra as [PITH_FULL_IMAGE:figures/full_fig_p016_5.png]
Figure 6
Figure 6. Figure 6: (a) Same spectrum of Per-emb 25 in [PITH_FULL_IMAGE:figures/full_fig_p017_6.png]
Figure 7
Figure 7. Figure 7: The same plots as [PITH_FULL_IMAGE:figures/full_fig_p018_7.png]
Figure 8
Figure 8. Figure 8: The same plots as [PITH_FULL_IMAGE:figures/full_fig_p019_8.png]
Figure 9
Figure 9. Figure 9: The same plots as [PITH_FULL_IMAGE:figures/full_fig_p020_9.png]

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Accretion Burst Crystallizes Silicates in a Planet-Forming Disk

    astro-ph.EP 2026-07 conditional novelty 7.0 of 10

    During an accretion burst of the embedded protostar EC 53, JWST mid-infrared spectra reveal newly appearing crystalline silicate emission, indicating in-situ thermal annealing of dust in the hot inner disk.

  2. Using Scattered Near-Infrared Light to Map Water Ice in Prestellar Cores with SPHEREx

    astro-ph.GA 2026-07 conditional novelty 7.0 of 10

    Coreshine SPHEREx spectra map 3 µm H2O ice across four prestellar cores; the two densest show an unexplained central drop in ice absorption that standard Bonnor-Ebert scattering models cannot reproduce.

Reference graph

Works this paper leans on

141 extracted references · 73 canonical work pages · cited by 2 Pith papers

  1. [1]

    , " * write output.state after.block = add.period write newline

    ENTRY address archivePrefix author booktitle chapter doi edition editor eprint howpublished institution journal key month number organization pages publisher school series title misctitle type volume year version url label extra.label sort.label short.list INTEGERS output.state before.all mid.sentence after.sentence after.block FUNCTION init.state.consts ...

  2. [2]

    write newline

    " write newline "" before.all 'output.state := FUNCTION format.url url empty "" new.block "" url * "" * if FUNCTION format.eprint eprint empty "" archivePrefix empty "" archivePrefix "arXiv" = new.block " " eprint * " " * new.block " " eprint * " " * if if if FUNCTION format.doi doi empty "" " " doi * " " * if FUNCTION format.pid doi empty eprint empty ur...

  3. [3]

    2012, , 538, A57

    Aikawa , Y., Kamuro , D., Sakon , I., et al. 2012, , 538, A57

    2012

  4. [4]

    F., Tychoniec , L., et al

    Beuther , H., van Dishoeck , E. F., Tychoniec , L., et al. 2023, , 673, A121

    2023

  5. [5]

    Boogert , A. C. A., Gerakines , P. A., & Whittet , D. C. B. 2015, , 53, 541

    2015

  6. [6]

    Boogert , A. C. A., Pontoppidan , K. M., Knez , C., et al. 2008, , 678, 985

    2008

  7. [7]

    Boogert , A. C. A., Huard , T. L., Cook , A. M., et al. 2011, , 729, 92

    2011

  8. [8]

    Bottinelli , S., Boogert , A. C. A., Bouwman , J., et al. 2010, , 718, 1100

    2010

Show all 141 references
  1. [9]

    Y., Sellgren , K., & Geballe , T

    Brooke , T. Y., Sellgren , K., & Geballe , T. R. 1999, , 517, 883

    1999

  2. [10]

    A., Belloche , A., Cabrit , S., Hennebelle , P., & Commer c on , B

    Busch , L. A., Belloche , A., Cabrit , S., Hennebelle , P., & Commer c on , B. 2020, , 633, A126

    2020

  3. [11]

    J., Lee , J.-E., & Bourke , T

    Chen , J.-H., Evans , II, N. J., Lee , J.-E., & Bourke , T. L. 2009, , 705, 1160

    2009

  4. [12]

    1999, , 351, 1066

    Dartois , E., Demyk , K., d'Hendecourt , L., & Ehrenfreund , P. 1999, , 351, 1066

    1999

  5. [13]

    2021, OpTool: Command-line driven tool for creating complex dust opacities , Astrophysics Source Code Library, record ascl:2104.010

    Dominik , C., Min , M., & Tazaki , R. 2021, OpTool: Command-line driven tool for creating complex dust opacities , Astrophysics Source Code Library, record ascl:2104.010

    2021

  6. [14]

    1995, , 300, 503

    Dorschner , J., Begemann , B., Henning , T., Jaeger , C., & Mutschke , H. 1995, , 300, 503

    1995

  7. [15]

    M., Crapsi , A., Evans , II, N

    Dunham , M. M., Crapsi , A., Evans , II, N. J., et al. 2008, , 179, 249

    2008

  8. [16]

    Ehrenfreund , P., Boogert , A. C. A., Gerakines , P. A., et al. 1996, , 315, L341

    1996

  9. [17]

    Ehrenfreund , P., Boogert , A. C. A., Gerakines , P. A., Tielens , A. G. G. M., & van Dishoeck , E. F. 1997, , 328, 649

    1997

  10. [18]

    L., Evans , II, N

    Enoch , M. L., Evans , II, N. J., Sargent , A. I., & Glenn , J. 2009, , 692, 973

    2009

  11. [19]

    J., Allen , L

    Evans , II, N. J., Allen , L. E., Blake , G. A., et al. 2003, , 115, 965

    2003

  12. [20]

    J., Allen , L

    Evans , II, N. J., Allen , L. E., Blake , G. A., et al. 2014, VizieR Online Data Catalog: c2d Spitzer final data release (DR4) (Evans+, 2003) , VizieR On-line Data Catalog: II/332. Originally published in: 2003PASP..115..965E

    2014

  13. [21]

    J., & van Dishoeck , E

    Fraser , H. J., & van Dishoeck , E. F. 2004, Advances in Space Research, 33, 14

    2004

  14. [22]

    T., & Herbst , E

    Garrod , R. T., & Herbst , E. 2006, , 457, 927

    2006

  15. [23]

    T., Widicus Weaver , S

    Garrod , R. T., Widicus Weaver , S. L., & Herbst , E. 2008, , 682, 283

    2008

  16. [24]

    A., Schutte , W

    Gerakines , P. A., Schutte , W. A., Greenberg , J. M., & van Dishoeck , E. F. 1995, , 296, 810

    1995

  17. [25]

    A., Whittet , D

    Gerakines , P. A., Whittet , D. C. B., Ehrenfreund , P., et al. 1999, , 522, 357

    1999

  18. [26]

    L., Whittet , D

    Gibb , E. L., Whittet , D. C. B., Boogert , A. C. A., & Tielens , A. G. G. M. 2004, , 151, 35

    2004

  19. [27]

    M., & Hong , S

    Greenberg , J. M., & Hong , S. S. 1974, in IAU Symposium, Vol. 60, Galactic Radio Astronomy, ed. F. J. Kerr & S. C. Simonson , 155

    1974

  20. [28]

    Hagen , W., Tielens , A. G. G. M., & Greenberg , J. M. 1983, , 51, 389

    1983

  21. [29]

    2018, , 869, 41

    He , J., Emtiaz , S., Boogert , A., & Vidali , G. 2018, , 869, 41

    2018

  22. [30]

    2010, , 48, 21

    Henning , T. 2010, , 48, 21

    2010

  23. [31]

    R., Roellig , T

    Houck , J. R., Roellig , T. L., van Cleve , J., et al. 2004, , 154, 18

    2004

  24. [32]

    M., Belloche , A., et al

    Hsieh , T.-H., Murillo , N. M., Belloche , A., et al. 2019, , 884, 149

    2019

  25. [33]

    A., & Palumbo , M

    Ioppolo , S., Sangiorgio , I., Baratta , G. A., & Palumbo , M. E. 2013, , 554, A34

    2013

  26. [34]

    2022, , 661, A80

    Jakobsen , P., Ferruit , P., Alves de Oliveira , C., et al. 2022, , 661, A80

    2022

  27. [35]

    Jin , M., & Garrod , R. T. 2020, , 249, 26

    2020

  28. [36]

    H., McClure , M

    Jin , M., Lam , K. H., McClure , M. K., et al. 2022, , 935, 133

    2022

  29. [37]

    J., & Tielens , A

    Kemper , F., Vriend , W. J., & Tielens , A. G. G. M. 2004, , 609, 826

    2004

  30. [38]

    J., Evans , II, N

    Kim , H. J., Evans , II, N. J., Dunham , M. M., Lee , J.-E., & Pontoppidan , K. M. 2012, , 758, 38

    2012

  31. [39]

    2022, , 935, 137

    Kim , J., Lee , J.-E., Jeong , W.-S., et al. 2022, , 935, 137

    2022

  32. [40]

    F., J rgensen , J

    Lahuis , F., van Dishoeck , E. F., J rgensen , J. K., Blake , G. A., & Evans , N. J. 2010, , 519, A3

    2010

  33. [41]

    A., & Evans , II, N

    Lee , J.-E., Bergin , E. A., & Evans , II, N. J. 2004, , 617, 360

    2004

  34. [42]

    J., Shirley , Y

    Lee , J.-E., Evans , II, N. J., Shirley , Y. L., & Tatematsu , K. 2003, , 583, 789

    2003

  35. [43]

    Lee , S., Lee , J.-E., & Bergin , E. A. 2015, , 217, 30

    2015

  36. [44]

    Madden , M. C. L., Boogert , A. C. A., Chiar , J. E., et al. 2022, , 930, 2

    2022

  37. [45]

    Marocco , F., Eisenhardt , P. R. M., Fowler , J. W., et al. 2021, , 253, 8

    2021

  38. [46]

    K., Rocha , W

    McClure , M. K., Rocha , W. R. M., Pontoppidan , K. M., et al. 2023, Nature Astronomy, 7, 431

    2023

  39. [47]

    F., Maillard , J.-P., Allen , M., Beer , R., & Belcourt , K

    Mitchell , G. F., Maillard , J.-P., Allen , M., Beer , R., & Belcourt , K. 1990, , 363, 554

    1990

  40. [48]

    2007, , 59, S369

    Murakami , H., Baba , H., Barthel , P., et al. 2007, , 59, S369

    2007

  41. [49]

    A., Fraser , H

    Noble , J. A., Fraser , H. J., Aikawa , Y., Pontoppidan , K. M., & Sakon , I. 2013, , 775, 85

    2013

  42. [50]

    I., Boogert , A

    \"O berg , K. I., Boogert , A. C. A., Pontoppidan , K. M., et al. 2008, , 678, 1032

    2008

  43. [51]

    I., Boogert , A

    \"O berg , K. I., Boogert , A. C. A., Pontoppidan , K. M., et al. 2011, , 740, 109

    2011

  44. [52]

    I., van Dishoeck , E

    \"O berg , K. I., van Dishoeck , E. F., Linnartz , H., & Andersson , S. 2010, , 718, 832

    2010

  45. [53]

    2007, , 59, S411

    Ohyama , Y., Onaka , T., Matsuhara , H., et al. 2007, , 59, S411

    2007

  46. [54]

    2021, , 916, 75

    Onaka , T., Kimura , T., Sakon , I., & Shimonishi , T. 2021, , 916, 75

    2021

  47. [55]

    2007, , 59, S401

    Onaka , T., Matsuhara , H., Wada , T., et al. 2007, , 59, S401

    2007

  48. [56]

    M., Fraser , H

    Pontoppidan , K. M., Fraser , H. J., Dartois , E., et al. 2003, , 408, 981

    2003

  49. [57]

    M., Boogert , A

    Pontoppidan , K. M., Boogert , A. C. A., Fraser , H. J., et al. 2008, , 678, 1005

    2008

  50. [58]

    A., Whittet , D

    Poteet , C. A., Whittet , D. C. B., & Draine , B. T. 2015, , 801, 110

    2015

  51. [59]

    2019, , 626, A118

    Qasim , D., Lamberts , T., He , J., et al. 2019, , 626, A118

    2019

  52. [60]

    H., Wright , G

    Rieke , G. H., Wright , G. S., B \"o ker , T., et al. 2015, , 127, 584

    2015

  53. [61]

    Rocha , W. R. M., McClure , M. K., Sturm , J. A., et al. 2025, , 693, A288

    2025

  54. [62]

    A., & Khanna , R

    Schutte , W. A., & Khanna , R. K. 2003, , 398, 1049

    2003

  55. [63]

    A., Boogert , A

    Schutte , W. A., Boogert , A. C. A., Tielens , A. G. G. M., et al. 1999, , 343, 966

    1999

  56. [64]

    2010, , 514, A12

    Shimonishi , T., Onaka , T., Kato , D., et al. 2010, , 514, A12

    2010

  57. [65]

    2021, VizieR Online Data Catalog: The Spitzer (SEIP) source list (SSTSL2) (Spitzer Science Center, 2021) , VizieR On-line Data Catalog: II/368

    Spitzer Science Center (SSC) , & Infrared Science Archive (IRSA) . 2021, VizieR Online Data Catalog: The Spitzer (SEIP) source list (SSTSL2) (Spitzer Science Center, 2021) , VizieR On-line Data Catalog: II/368. Originally published in: Spitzer Science Center (SSC), IRSA (2021)

    2021

  58. [66]

    M., Min , M., Chiar , J

    van Breemen , J. M., Min , M., Chiar , J. E., et al. 2011, , 526, A152

    2011

  59. [67]

    A., van Dishoeck , E

    van Kempen , T. A., van Dishoeck , E. F., Hogerheijde , M. R., & G \"u sten , R. 2009, , 508, 259

    2009

  60. [68]

    W., Roellig , T

    Werner , M. W., Roellig , T. L., Low , F. J., et al. 2004, , 154, 1

    2004

  61. [69]

    D., Pontoppidan , K

    Yang , Y.-L., Green , J. D., Pontoppidan , K. M., et al. 2022, , 941, L13

    2022

  62. [70]

    2021, , 919, 116

    Yoon , S.-Y., Lee , J.-E., Lee , S., et al. 2021, , 919, 116

    2021

  63. [71]

    M., et al

    Zasowski , G., Kemper , F., Watson , D. M., et al. 2009, , 694, 459

    2009

  64. [72]

    Aikawa, Y., Kamuro, D., & Sakon, I. et al. 2012, AKARI Observations of Ice Absorption Bands towards Edge-on Young Stellar Objects, A&A, 538, A57

    2012

  65. [73]

    F., & Tychoniec, L

    Beuther, H., van Dishoeck, E. F., & Tychoniec, L. et al. 2023, JWST Observations of Young Protostars (JOYS) Outflows and Accretion in the High-mass Star-forming Region IRAS 23385+6053, A&A, 673, A121

    2023

  66. [74]

    Boogert, A. C. A., Gerakines, P. A., & Whittet, D. C. B. 2015, Observations of The Icy Universe, ARA&A, 53, 541

    2015

  67. [75]

    Boogert, A. C. A., Huard, T. L., & Cook, A. M. et al. 2011, Ice and Dust in The Quiescent Medium of Isolated Dense Cores, ApJ, 729, 92

    2011

  68. [76]

    Boogert, A. C. A., Pontoppidan, K. M., & Knez, C. et al. 2008, The c2d Spitzer Spectroscopic Survey of Ices around Low-mass Young Stellar Objects. 1 . H2O and The 5 - 8 Bands, ApJ, 678, 985

    2008

  69. [77]

    Bottinelli, S., Boogert, A. C. A., & Bouwman, J. et al. 2010, The c2d Spitzer Spectroscopic Survey of Ices around Low-mass Young Stellar Objects. 4 . NH3 and CH3OH , ApJ, 718, 1100

    2010

  70. [78]

    Y., Sellgren, K., & Geballe, T

    Brooke, T. Y., Sellgren, K., & Geballe, T. R. 1999, New 3 Micron Spectra of Young Stellar Objects with H2O Ice Bands, ApJ, 517, 883

    1999

  71. [79]

    A., Belloche, A., Cabrit, S., Hennebelle, P., & Commerçon, B

    Busch, L. A., Belloche, A., Cabrit, S., Hennebelle, P., & Commerçon, B. 2020, The dynamically young outflow of the Class 0 protostar Cha-MMS1, A&A 633, A126

    2020

  72. [80]

    Chen, J.-H., Evans, N. J. 2 , Lee, J.-E., Bourke, T. L. 2009, The Spitzer c2d Survey of Nearby Dense Cores. VII. Chemistry and Dynamics in L43, ApJ, 705, 1160

    2009

  73. [81]

    Chu, L. E. U., Hodapp, K., & Boogert, A. C. A. 2020, Observations of the Onset of Complex Organic Molecule Formation in Interstellar Ices, ApJ, 904, 86

    2020

  74. [82]

    1999, Carbon Dioxide-methanol Intermolecular Complexes in Interstellar Grain Mantles, A&A, 351, 1066

    Dartois, E., Demyk, K., d'Hendecourt, L., & Ehrenfreund, P. 1999, Carbon Dioxide-methanol Intermolecular Complexes in Interstellar Grain Mantles, A&A, 351, 1066

    1999

  75. [83]

    2021, OpTool: Command-line Driven Tool for Creating Complex Dust Opacities, Astrophysics Source Code Library, ascl:2104.010

    Dominik, C., Min, M., & Tazaki, R. 2021, OpTool: Command-line Driven Tool for Creating Complex Dust Opacities, Astrophysics Source Code Library, ascl:2104.010

    2021

  76. [84]

    1995, Steps toward Interstellar Silicate Mineralogy

    Dorschner, J., Begemann, B., Henning, T., Jaeger, C., & Mutschke, H. 1995, Steps toward Interstellar Silicate Mineralogy. 2 . Study of Mg-Fe-Silicate Glasses of Variable Composition, A&A, 300, 503

    1995

  77. [85]

    M., Crapsi, A., & Evans, N

    Dunham, M. M., Crapsi, A., & Evans, N. J. 2 . et al. 2008, Identifying the Low-luminosity population of Embedded Protostars in the c2d Observations of Clouds and Cores, ApJS, 179, 249

    2008

  78. [86]

    Ehrenfreund, P., Boogert, A. C. A., & Gerakines, P. A. et al. 1996, A Laboratory Database of Solid CO and CO2 for ISO, A&A, 315, L341

    1996

  79. [87]

    Ehrenfreund, P., Boogert, A. C. A., & Gerakines, P. A. et al. 1997, Infrared Spectroscopy of Interstellar Apolar Ice Analogs, A&A, 328, 649

    1997

  80. [88]

    L., Evans, N

    Enoch, M. L., Evans, N. J. 2 , Sargent, A. I., & Glenn, J. 2009, Properties of the Youngest Protostars in Perseus, Serpens, and Ophiuchus, ApJ, 692, 973

    2009

  81. [89]

    Evans, N. J. 2 , Allen, L. E., & Blake, G. A. et al. 2003, From Molecular Cores to Planet-forming Disks: An SIRTF Legacy Program, PASP, 115, 965

    2003

  82. [90]

    Evans, N. J. 2 , Allen, L. E., & Blake, G. A. et al. 2014, VizieR Online Data Catalog: c2d Spitzer final data release (DR4) (Evans+, 2003), VizieR On-line Data Catalog, II/332

    2014

  83. [91]

    Fraser, H. J. & van Dishoeck, E. F. 2004, SURFRESIDE: A Novel Experiment to Study Surface Chemistry under Interstellar and Protostellar Conditions, AdSpR, 33, 14

    2004

  84. [92]

    Garrod, R. T. & Herbst, E. 2006, Formation of Methyl Formate and Other Organic Species in the Warm-up Phase of Hot Molecular Cores, A&A, 457, 927

    2006

  85. [93]

    T., Widicus Weaver, S

    Garrod, R. T., Widicus Weaver, S. L., & Herbst, E. 2008, Complex Chemistry in Star-forming Regions: An Expanded Gas-grain Warm-up Chemical Model, ApJ, 682, 283

    2008

  86. [94]

    A., Schutte, W

    Gerakines, P. A., Schutte, W. A., Greenberg, J. M., & van Dishoeck, E. F. 1995, The Infrared Band Strengths of H2O , CO , and CO2 in Laboratory Simulations of Astrophysical Ice Mixtures, A&A, 296, 810

    1995

  87. [95]

    A., Whittet, D

    Gerakines, P. A., Whittet, D. C. B., & Eherenfreund, P. et al. 1999, Infrared Space Observatory with The Observations of Solid Carbon Dioxide in Molecular Clouds, ApJ, 522, 357

    1999

  88. [96]

    L., Whittet, D

    Gibb, E. L., Whittet, D. C. B., Boogert, A. C. A., & Tielens, A. G. G. M. 2004, Interstellar Ice: The Infrared Space Observatory Legacy, ApJS, 151, 35

    2004

  89. [97]

    Greenberg, J. M. & Hong, S.-S. 1974, The Chemical Composition and Distribution of Interstellar Grains, in IAU Symp. 60, Galactic Radio Astronomy, ed. F.J. Kerr & S. C. Simonson (Cambridge: Cambridge Univ. Press), 155

    1974

  90. [98]

    Hagen, W., Tielens, A. G. G. M., & Greenberg, J. M. 1983, A&AS, 51, 389

    1983

  91. [99]

    M., Boogert, A., & Vidali, G

    He, J., Emtiaz, S. M., Boogert, A., & Vidali, G. 2018, The ^ 12 CO2 and ^ 13 CO2 Absorption Bands as Tracers of the Thermal History of Interstellar Icy Grain Mantles, ApJ, 869, 41

    2018

  92. [100]

    2010, Cosmic Silicates, ARA&A, 48, 21

    Henning, T. 2010, Cosmic Silicates, ARA&A, 48, 21

    2010

  93. [101]

    R., Roellic, T

    Houck, J. R., Roellic, T. L., & van Cleve, J. et al. 2004, The Infrared Spectrograph (IRS) on The Spitzer Space Telescope, ApJS, 154, 18

    2004

  94. [102]

    M., & Belloche, A

    Hsieh, T.-H., Murillo, N. M., & Belloche, A. et al. 2019, Chronology of Episodic Accretion in Protostars - An ALMA Survey of the CO and H2O Snowlines, ApJ, 884, 149

    2019

  95. [103]

    A., & Palumbo, M

    Ioppolo, S., Sangiorgio, I., Baratta, G. A., & Palumbo, M. E. 2013, Solid CO2 in Low-mass Young Stellar Objects: Comparison between Spitzer and Laboratory Spectra, A&A, 554, A34

    2013

  96. [104]

    Jakobsen, P., Ferruit, P., & de Oliveira, C. A. et al. 2022, The Near-Infrared Spectrograph (NIRSpec) on the James Webb Space Telescope 1 . Overview of the Instrument and Its Capabilities, A&A, 661, A80

    2022

  97. [105]

    Jin, M & Garrod, R. T. 2020, Formation of Complex Organic Molecules in Cold Interstellar Environments through Nondiffusive Grain-surface and Ice-mantle Chemistry, ApJS, 249, 26

    2020

  98. [106]

    H., & McClure, M

    Jin, M., Lam, K. H., & McClure, M. K. et al. 2022, Ice Age: Chemodynamical Modeling of Cha-MMS1 to Predict New Solid-phase Species for Detection with JWST, ApJ, 935, 133

    2022

  99. [107]

    J., & Tielens, A

    Kemper, F., Vriend, W. J., & Tielens, A. G. G. M. 2004, The Absence of Crystalline Silicates in The Diffuse Interstellar Medium, ApJ, 609, 826

    2004

  100. [108]

    J., Evans, N

    Kim, H. J., Evans, N. J. 2 ., Dunham, M. M., Lee, J.-E., & Pontoppidan, K. M. 2012, CO2 Ice toward Low-luminosity Embedded Protostars: Evidence for Episodic Mass Accretion via Chemical History, ApJ, 758, 38

    2012

  101. [109]

    & Jeong, W.-S

    Kim, J., Lee, J.-E. & Jeong, W.-S. et al. 2022, Ice Features of Low-luminosity Protostars in Near-infrared Spectra of AKARI/IRC, ApJ, 935, 137

    2022

  102. [110]

    F., Jørgensen, J

    Lahuis, F., van Dishoeck, E. F., Jørgensen, J. K, Blake, G. A., & Evans, N. J. 2 . 2010, c2d Spitzer IRS spectra of embedded low-mass young stars: gas-phase emission lines, A&A, 519, A3

    2010

  103. [111]

    A., & Evans, N

    Lee, J.-E., Bergin, E. A., & Evans, N. J. 2 . 2004, Evolution of Chemistry and Molecular Line Profiles During Protostellar Collapse, ApJ, 617, 360

    2004

  104. [112]

    Lee, J.-E., Evans, N. J. 2 ., Shirley, Y. L., & Tatematsu, K. 2003, Chemistry and Dynamics in Pre-Protostellar Cores, ApJ, 583, 789

    2003

  105. [113]

    Lee, S., Lee, J.-E., & Bergin, E. A. 2015, The Warm CO Gas along the UV-heated Outflow Cavity Walls: A Possible Interpretation for the Herschel/PACS CO Spectra of Embedded YSOs, ApJS, 217, 30

    2015

  106. [114]

    K., Rocha, W

    McClure, M. K., Rocha, W. R. M., & Pontoppidan, K. M. et al. 2023, An Ice Age JWST Inventory of Dense Molecular Cloud Ices, NatAs, 7, 431

    2023

  107. [115]

    Madden, M. C. L., Boogert, A. C. A., & Chiar, J. E. et al. 2022, Infrared Spectroscopic Survey of the Quiescent Medium of Nearby Clouds. 2 . Ice Formation and Grain Growth in Perseus and Serpens, ApJ, 930, 2

    2022

  108. [116]

    Marocco, F., Eisenhardt, P. R. M., & Fowler, J. W. et al. 2021, The CatWISE2020 Catalog, ApJS, 253, 8

    2021

  109. [117]

    F., Maillard, J.-P., Allen, M., Beer, R., & Belcourt, K

    Mitchell, G. F., Maillard, J.-P., Allen, M., Beer, R., & Belcourt, K. 1990, Hot and Cold Gas toward Young Stellar Objects, ApJ, 363, 554

    1990

  110. [118]

    Murakami, H., Baba, H., & Barthel, P. et al. 2007, The Infrared Astronomical Mission AKARI, PASJ, 59, 369

    2007

  111. [119]

    A., Fraser, H

    Noble, J. A., Fraser, H. J., & Aikawa, Y. et al. 2013, A Survey of H2O , CO2 , and CO Ice Features toward Background Stars and Low-mass Young Stellar Objects using AKARI, ApJ, 775, 85

    2013

  112. [120]

    I., Boogert, A

    O berg, K. I., Boogert, A. C. A., & Potoppidan, K. M., et al. 2008, The c2d Spitzer Spectroscopic Survey of Ices around Low-mass Young Stellar Objects. 3 . CH4 , ApJ, 678, 1032

    2008

  113. [121]

    I., Boogert, A

    O berg, K. I., Boogert, A. C. A., & Potoppidan, K. M., et al. 2011, The Spitzer Ice Legacy: Ice Evolution from Cores to Protostars, ApJ, 740, 109

    2011

  114. [122]

    I., van Dishoeck, E

    O berg, K. I., van Dishoeck, E. F., Linnartz, H., & Andersson, S. 2010, The Effect of H2O on Ice Photochemistry, ApJ, 718, 832

    2010

  115. [123]

    Onaka, T., Matsuhara, H., & Wada, T. et al. 2007, The Infrared Camera (IRC) for AKARI - Design and Imaging Performance, PASJ, 59, 401

    2007

  116. [124]

    2021, Discovery of Two Infrared Objects with Strong Ice Absorption in the AKARI Slitless Spectroscopic Survey of the Galactic Plane, ApJ, 916, 75

    Onaka, T., Kimura, T., Sakon, I., & Shimonishi, T. 2021, Discovery of Two Infrared Objects with Strong Ice Absorption in the AKARI Slitless Spectroscopic Survey of the Galactic Plane, ApJ, 916, 75

    2021

  117. [125]

    Ohyama, Y., Onaka, T., & Matsuhara, H. et al. 2007, Near-Infrared and Mid-Infrared Spectroscopy with the Infrared Camera (IRC) for AKARI, PASJ, 59, 411

    2007

  118. [126]

    M., Boogert, A

    Pontoppidan, K. M., Boogert, A. C. A., & Fraser, H. J., et al. 2008, The c2d Spitzer Spectroscopic Survey of Ices around Low-mass Young Stellar Objects. 2 . CO2 , ApJ, 678, 1005

    2008

  119. [127]

    M., Fraser, H

    Pontoppidan, K. M., Fraser, H. J., & Dartois, E., et al. 2003, A 3 - 5 VLT Spectroscopic Survey of Embedded Young Low Mass Stars 1 . Structure of the CO Ice, A&A, 408, 981

    2003

  120. [128]

    A., Whittet, D

    Poteet, C. A., Whittet, D. C. B., & Draine, B. T. 2015, The Composition of Interstellar Grains toward Ophiuchi: Constraining The Elemental Budget Near The Diffuse-dense Cloud Transition, ApJ, 801, 110

    2015

  121. [129]

    Qasim, D., Lamberts, T., & He, J. et al. 2019, Extension of the HCOOH and CO2 solid-state reaction network during the CO freeze-out stage: inclusion of H2CO , A&A, 626, A118

    2019

  122. [130]

    H., Wright, G

    Rieke, G. H., Wright, G. S., & B o ker, T. et al. 2015, The Mid-Infrared Instrument for the Jame Webb Space Telescope, 1 : Introduction, PASP, 127, 584

    2015

  123. [131]

    Rocha, W. R. M., McClure, M. K., Sturm, J. A. et al. 2025, Ice inventory towards the protostar Ced 110 IRS4 observed with the James Webb Space Telescope: Results from the Early Release Science Ice Age program, A&A, 693, A288

    2025

  124. [132]

    A., Boogert, A

    Schutte, W. A., Boogert, A. C. A., & Tielens, A. G. G. M. et al. 1999, Weak Ice Absorption Features at 7.24 and 7.41 in The Spectrum of Obscured Young Stellar Object W 33A, A&A, 343, 966

    1999

  125. [133]

    Schutte, W. A. & Khanna, R. K. 2003, Origin of The 6.85 Band Near Yong Stellar Objects: The Ammonium Ion ( NH4+ ) Revisited, A&A, 398, 1049

    2003

  126. [134]

    Spitzer Science Center, (SSC) and Infrared Science Archive, (IRSA) 2021, The Spitzer (SEIP) source list (SSTSL2), 2021yCat.2368....0S

    2021

  127. [135]

    2010, Spectroscopic Observations of Ices around Embedded Young Stellar Objects in the Large Magellanic Cloud with AKARI, A&A, 514, A12

    Shimonishi, T., Onaka, T., Kato, D., Sakon, I., Ita, Y., Kawamura, A., & Kaneda, H. 2010, Spectroscopic Observations of Ices around Embedded Young Stellar Objects in the Large Magellanic Cloud with AKARI, A&A, 514, A12

    2010

  128. [136]

    M., Min, M., & Chiar, J

    van Breemen, J. M., Min, M., & Chiar, J. E. et al. 2011, The 9.7 and 18 Silicate Absorption Profiles towards Diffuse and Molecular Cloud Lines-of-sight, A&A, 526, A152

    2011

  129. [137]

    A., van Dishoeck, E

    van Kempen, T. A., van Dishoeck, E. F., Hogerheijde, M. R. and G u sten, R. 2009, Dense and Warm Molecular Gas in the Envelopes and Outflows of Southern Low-mass Protostars, A&A, 508, 259

    2009

  130. [138]

    W., Roellic, T

    Werner, M. W., Roellic, T. L., & Low, F. J. et al. 2004, The Spitzer Space Telescope Mission, ApJS, 154, 1

    2004

  131. [139]

    D., & Pontoppidan, K

    Yang, Y.-L., Green, J. D., & Pontoppidan, K. M. et al. 2022, CORINOS. 1 . JWST/MIRI Spectroscopic and Imaging of a Class 0 Protostar IRAS 15398 - 3359, ApJL, 941, L13

    2022

  132. [140]

    Yoon, S.-Y., Lee, J.-E., & Lee, S. et al. 2021, Evidence of Accretion Burst: The Viscously Heated Inner Disk of the Embedded Protostar IRAS 16316-1540, ApJ, 919, 116

    2021

  133. [141]

    & Watson, D

    Zasowski, G., Kemper, F. & Watson, D. M. et al. 2009, Spitzer Infrared Spectrograph Observations of Class 1 / 2 Objects in Taurus: Composition and Thermal History of The Circumstellar Ices, ApJ, 694, 459

    2009

Pith tools

Reviewed August 15, 2026 · model on record in the stance chip above.