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This paper claims that sixteen alcohols, thiols, and their aldehyde and thioaldehyde precursors bind to amorphous solid water ice with a distribution of binding energies rather than a single value, and that rate-equation models which incorp

Reviewed by Pith at T0; open to challenge. T0 means a machine referee read the full paper against a public rubric. the ladder, T0–T4 →

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Quantum chemical binding energy distributions are reported for 16 O/S-bearing species on amorphous water ice, and using these distributions alters modeled ice-phase abundances.

T0 review reviewed 2026-08-05 challenge →

load-bearing objection Useful new binding energies for a few sulfur and oxygen species, but the paper's 'distributions' are scaling-factor extrapolations from H2CO, so the widths are not independently grounded. the 2 major comments →

arxiv 2509.00431 v1 pith:ZZWZBVD6 submitted 2025-08-30 astro-ph.GA astro-ph.SR

Binding energy distributions of alcohols, thiols, and their precursors on interstellar water ice surfaces

Arghyadeb Roy , Ankan Das , Milan Sil , Prasanta Gorai , Kenji Furuya , Naoki Nakatani , Takashi Shimonishi This is my paper
classification astro-ph.GA astro-ph.SR
keywords binding energy distributionamorphous solid wateralcoholsthiolsinterstellar ice chemistryastrochemical modelingsulfur chemistryrate equation model
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved

The pith

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

The reading

Interstellar chemistry models usually give each molecule a single binding energy on dust-grain ice, even though real amorphous water ice offers many adsorption sites with different strengths. This paper computes binding energies for sixteen species — the monohydric alcohols methanol through n-propanol, their sulfur analogues the thiols, and the radical and aldehyde/thioaldehyde precursors that build them — on clusters of twenty water molecules representing amorphous solid water, and reports each species' binding energy as a Gaussian distribution rather than one number. The authors then feed those distributions into a rate-equation gas-grain model and find that predicted ice-phase abundances shift noticeably relative to the standard single-binding-energy treatment, most strongly for volatile species such as CO and methanol. The work also provides first-time binding energies for n-propanol, ethanethiol, and n-propanethiol on water ice, and a general rule that sulfur-bearing analogues bind more weakly than their oxygen counterparts, with consequences for which surface reactions dominate alcohol and thiol formation.

Core claim

On the paper's own terms, the discovery is that a molecule's binding energy on amorphous solid water is a distribution, not a number, and that for these species the distribution is wide enough to change model outcomes. Using ωB97X-D DFT with BSSE corrections on nine [H2O]20 amorphous water clusters, the authors report a Gaussian mean and spread for each species — 5178±1343 K for methanol, 3652±974 K for methanethiol — built by scaling the highest computed binding energy by 1.172 and the site spread by 2.385, factors anchored to formaldehyde and to the prior diatomic-radical study. In a rate-equation model with binding-energy probability densities, these distributions shift predicted ice-phas

What carries the argument

The central object is the binding-energy distribution: a Gaussian defined by a mean and a standard deviation per species. The mean comes from the highest-energy adsorption site on the most stable [H2O]20 cluster (ASW(1)), scaled by 1.172 — the ratio of the average formaldehyde binding energy over all nine clusters to its highest ASW(1) value — and the width comes from the site-to-site spread on ASW(1) multiplied by 2.385, a factor adopted from Sil et al. (2024). Adsorption sites are the dangling-hydrogen (d-H) and dangling-oxygen (d-O) positions on the cluster surfaces, selected by electrostatic complementarity. The machinery converts one expensive calculation per species into a full distrib

Load-bearing premise

The load-bearing premise is that scaling factors taken from one molecule — 1.172 from formaldehyde's cluster-to-cluster average and 2.385 from the earlier diatomic-radical study — apply unchanged to the other fifteen species, so that a single molecule's surface-morphology statistics stand in for everyone else's.

What would settle it

Take a second species, say thioformaldehyde or methanol, and compute its binding energy over all 75 dangling-hydrogen sites across the nine [H2O]20 clusters exactly as the paper did for formaldehyde; if the ratio of the average to the highest binding energy departs substantially from 1.172 (or the spread ratio from 2.385), the reported distributions are an artifact of the scaling. A temperature-programmed desorption experiment measuring the desorption-energy width of ethanethiol or n-propanol on amorphous solid water would independently settle the predicted distribution widths.

Watch this falsifier. Get emailed when new claim-graph text bears on it.

If this is right

  • Methanol formation is predicted to proceed mainly via CH3O + H, since CH3O binds loosely enough to diffuse on the ice while CH2OH binds tightly and stays put; for methanethiol, CH3S and CH2SH contribute comparably.
  • First-time binding energies for n-propanol, ethanethiol, and n-propanethiol on water ice give modelers values where previously only gold-surface extrapolations existed.
  • Rate-equation models with binding-energy distributions predict different ice-phase abundances than single-value models at 10–20 K, with CO and methanol most affected; the authors expect larger deviations above 100 K when ices sublimate.
  • The modeled network does not yet include the formation routes of the higher alcohols and thiols themselves, nor the binding-energy spread of hydrogen atoms — the authors cite the omitted H-atom distribution as the reason their methanol trend differs from the earlier REPDF study.
  • Oxygen-bearing species systematically out-bind their sulfur analogues, so the two families will desorb at different temperatures and enter the gas phase at different stages of a warm-up.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The scaling shortcut is testable as stated: recomputing all nine clusters' sites for a second molecule, such as thioformaldehyde (which the paper considered but rejected for lacking an experimental anchor), would show whether the 1.172 mean factor and 2.385 width factor are portable or species-specific.
  • If the predicted widths hold, thermal desorption from interstellar ice analogues should show broad, multi-peak signatures rather than sharp monolayer desorption peaks; laboratory temperature-programmed desorption of ethanethiol or n-propanol on amorphous solid water would be a direct check.
  • The consistent O-over-S binding gap implies that sulfur-bearing ices are released to the gas phase earlier than oxygen-bearing ones during warm-up, which could sharpen predictions for when gas-phase sulfur chemistry turns on in star-forming regions.
  • The Gaussian shape is an assumed convenience; real binding-site populations on porous ice may be skewed or bimodal, and the same modeling framework would inherit whatever shape the site statistics actually take.
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Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

2 major / 7 minor

Summary. This paper computes binding energies (BEs) for 16 interstellar species — CO, HCO, H2CO, the alcohol families (CH3O, CH2OH, CH3OH, C2H5OH, n-C3H7OH) and their sulfur analogues (CS, HCS, H2CS, CH3S, CH2SH, CH3SH, C2H5SH, n-C3H7SH) — on [H2O]20 amorphous solid water clusters at the ωB97X-D/6-311+G(d,p) level with counterpoise BSSE and harmonic ZPE corrections. H2CO is sampled over nine ASW clusters (75 dangling-H sites) and fitted to a Gaussian. For the other fifteen species, the highest BE on the single ASW(1) cluster is multiplied by 1.172 (a factor calibrated to H2CO) and the intra-cluster site-spread σ is multiplied by 2.385 (from Sil et al. 2024) to construct Gaussian BE distributions. These distributions are compared with databases and experiments and then implemented in the REPDF rate-equation model of Furuya (2024); dark-cloud runs at 10/15/20 K show abundance differences relative to the single-BE RE model, mainly for CO and methanol.

Significance. The paper targets a genuine gap: astrochemical models increasingly need BE distributions rather than single values, and systematic multi-site data for alcohols, thiols, and their precursors on ASW are scarce. If the constructed distributions are reliable, Table 1 would be a useful community resource. The paper has real strengths: the DFT level with BSSE and ZPE corrections is standard; the nine-cluster, 75-site H2CO sampling is a genuine distribution; the scaling construction is described transparently in §3.1; coordinates are openly deposited on GitHub; and five experimental benchmarks (CO, H2CO, CH3OH, C2H5OH, CH3SH) are used. However, the distributional claim for 15 of the 16 species rests on scaling factors whose species independence is not tested, so the significance of the §4 model implications is conditional on that assumption.

major comments (2)
  1. [§3.1, Tables A.2–A.4 and Table 1] The BE distributions for 15 of the 16 species are not sampled over the nine ASW clusters. The mean is the highest +BSSE BE on ASW(1) multiplied by 1.172, a factor calibrated to H2CO alone; the σ is the ASW(1) site-spread multiplied by 2.385 from Sil et al. (2024). This assumes both factors are species-independent. The assumption is most fragile for the alcohols/thiols, which bind through d-O sites as H-bond donors (–OH/–SH), a binding mode H2CO does not exercise. Since the REPDF results in §4 use these μ/σ values (e.g., CH2OH 5354±2111 K, CH3SH 3652±974 K), the distributional claim and the model implications rest on this untested transfer. I request validation: sample at least CH3OH and CH3SH over all nine clusters, or provide a sensitivity analysis; at minimum, tabulate the unscaled ASW(1) values separately from the scaled values.
  2. [§3.1, Fig. 2, Table 1] The σ-scaling factor 2.385 is carried over from Sil et al. (2024), which treated diatomic radicals; its applicability to polyatomic closed-shell species is asserted without justification. In addition, the paper presents two different H2CO distributions: the Gaussian fit to all 75 sites (Fig. 2) has μ=2820, σ=605 K, while Table 1 and the model use 3696±663 K, the mean/spread of the nine per-cluster maxima. For H2CO, 663 K numerically equals the ASW(1) site-spread (≈278 K) times 2.385, but the manuscript never explains this or states which σ the REPDF runs actually use. Please clarify the relationship between the fitted distribution and the distribution used in the model, and justify (or re-derive) the 2.385 transfer to the polyatomic, d-O-binding species.
minor comments (7)
  1. [Abstract and §4] The claimed 'significant effects on predicted abundances' are demonstrated only for a subset: Fig. 6 shows eight of the sixteen computed species, and the new thiols and n-propanol do not enter the network at all. The conclusion acknowledges this scope limitation, but the abstract and introduction should too.
  2. [Fig. 5 and §4] The REPDF setup includes OH and CH3, but their BE-distribution parameters are not given in Table 1 or in the text; their source should be stated (e.g., Furuya 2024 or Sil et al. 2024).
  3. [§3.2, Table 1 (CH3SH)] The computed 3652±974 K is about 1000 K below the recent experimental value of 4640±170 K (Narayanan et al. 2025), yet the discrepancy is not discussed even though CH3SH is one of only five species with experimental data.
  4. [§3.1] 'a uniform distribution favouring the highest BE site below 10 K' is contradictory as written; presumably a Boltzmann weighting of sites is meant.
  5. [§3.1] 'CS exhibits a higher BE than CO, primarily due to its lower dispersive nature' — CS is more polarizable than CO, so 'lower dispersive nature' appears to be a slip and should be reworded.
  6. [§4] 'In contrast, the RE model also includes the minimum and maximum BE values' should read REPDF; as written it contradicts the preceding sentence defining RE as single-BE.
  7. [Fig. 2] The claim that the H2CO data 'closely follows a Gaussian' rests on visual inspection of 75 binned values; a goodness-of-fit test would strengthen the statement and is quick to add.

Circularity Check

0 steps flagged

No significant circularity: BE distributions are transparent rescaling of ASW(1) calculations, not derivations from the claimed outputs

full rationale

The paper's BE distributions are not circular. The H2CO distribution is derived directly from 75 d-H binding energies across nine ASW clusters (Table A.1), giving μ = 2820 K and σ = 605 K for the raw site distribution, and an average-of-cluster-maxima value of 3696 K reported in Table 1. For the other 15 species, the paper transparently computes BEs on the ASW(1) cluster only and then rescales the highest site BE by 1.172 and the site-to-site spread by 2.385 (from Sil et al. 2024) to approximate cluster-morphology variation. This is an extrapolation assumption, not a logical reduction: the reported μ and σ are not fit to or defined by the abundances the model later predicts, nor are they obtained by inverting the target results. The model comparison (RE vs REPDF) is a sensitivity analysis: inputting broader BE distributions changes desorption and ice chemistry, which is the expected mechanism, not a tautology. The 1.172 factor is calibrated to H2CO, and the 2.385 factor comes from a prior same-group paper, but neither factor is derived from the species whose abundance is being predicted, so the central claim retains independent content. The weakness flagged by the skeptic is a question of transferability/validity of the scaling factors, not circularity.

Axiom & Free-Parameter Ledger

6 free parameters · 4 axioms · 0 invented entities

The main free parameters are scaling factors that convert single-cluster, single-site BEs into claimed distributions. These are fit to H2CO or taken from prior work by the same group, and are applied to all other species without per-species validation.

free parameters (6)
  • Mean BE scaling factor (+BSSE) = 1.172
    Derived as ratio of average BE to the highest BE for H2CO across nine ASW clusters; applied to all other non-diatomic species.
  • Mean BE scaling factor (-BSSE) = 1.200
    Same ratio as above for uncorrected BSSE values.
  • Standard deviation scaling factor = 2.385
    Taken from Sil et al. (2024); multiplies the standard deviation of BE over ASW(1) binding sites to estimate overall cluster morphological spread.
  • Diatomic BE scaling factor (+BSSE) = 1.177
    From Sil et al. (2024) for diatomic species; applied to CO and CS.
  • Diatomic standard deviation scaling factor = 0.721
    From Sil et al. (2024) for diatomic species; applied to CO and CS.
  • H2CO Gaussian mean and sigma = mu=2820 K, sigma=605 K
    Fit to 75 d-H binding sites across nine clusters, but the model uses 3696 K as the mean, creating a mismatch.
axioms (4)
  • domain assumption DFT omegaB97X-D/6-311+G(d,p) reliably describes adsorption energies and radicals on water ice.
    Invoked in Section 2 as the computational level; accuracy is assumed from prior studies.
  • domain assumption [H2O]20 clusters represent amorphous solid water surfaces.
    Used throughout; the clusters are inherited from Sil et al. (2024) and assumed to capture ASW heterogeneity.
  • domain assumption Binding energy distribution is Gaussian.
    Section 3.1 fits a Gaussian to H2CO and assumes Gaussian form for all species.
  • domain assumption At low temperature, molecules occupy the highest-BE site (Boltzmann limit).
    Section 3.1 justifies using the average of the highest d-H sites per cluster as the representative BE.

reviewed 2026-08-05 · how reviews work

0 comments
Cite this review

Pith. "Pith review of Binding energy distributions of alcohols, thiols, and their precursors on interstellar water ice surfaces." pith.science (2026). https://pith.science/paper/ZZWZBVD6

@misc{pith2026250900431,
  author       = {Pith},
  title        = {Pith review of: Binding energy distributions of alcohols, thiols, and their precursors on interstellar water ice surfaces},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/ZZWZBVD6}},
  note         = {Machine review of arXiv:2509.00431}
}
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read the original abstract

Binding energy (BE) is a critical parameter in astrochemical modeling, governing the retention of species on interstellar dust grains and their subsequent chemical evolution. However, conventional models often rely on single-valued BEs, overlooking the intrinsic distribution arising from diverse adsorption sites. In this study, we present BEs for monohydric alcohols, thiols, and their plausible precursors, including aldehydes and thioaldehydes. We incorporate a distribution of BEs to capture the realistic variation in adsorption strengths. The quantum chemical calculations provide a range of BE values rather than a single estimate, ensuring a more precise description of molecular diffusion and surface chemistry. The BE trend of analogous species provides qualitative insight into the dominant reaction pathways and key precursors that drive the formation of larger molecules under interstellar conditions. Oxygen-bearing species generally exhibit higher BEs than their sulfur analogues, primarily due to stronger interactions, further influencing molecular adsorption and reactivity. We implemented BE distributions in astrochemical models, revealing significant effects on predicted abundances and establishing a more accurate framework for future astrochemical modeling.

Figures

Figures reproduced from arXiv: 2509.00431 by Ankan Das, Arghyadeb Roy, Kenji Furuya, Milan Sil, Naoki Nakatani, Prasanta Gorai, Takashi Shimonishi.

Figure 1
Figure 1. Figure 1: The most stable structures of formaldehyde, thioformaldehyde, and their corresponding radicals as precursors, along with the monohydric alcohols and thiol analogues (top) and the most stable ASW [H2O]20 cluster structure (bottom). The other ASW clusters with their relative energies are available in the appendix (available on Zenodo) of Sil et al. (2024). Red, white, grey, and yellow balls represent Oxygen,… view at source ↗
Figure 2
Figure 2. Figure 2: Gaussian distribution for the +BSSE BE values of H2 CO over the 75 d-H binding sites across the nine ASW [H2O]20 clusters. ical systems. Harmonic vibrational frequency (unscaled) anal￾ysis confirmed local minima, and zero-point energy (ZPE) cor￾rections were applied. Basis Set Superposition Error (BSSE) was corrected using the CounterPoise method, where the cor￾rected BE is obtained by subtracting BSSE fro… view at source ↗
Figure 3
Figure 3. Figure 3: BE trend for the O− and S−bearing analogue species on [H2O]20 clusters. comparable BE, indicating that multiple pathways may be vi￾able under interstellar conditions. 3.2. Comparison of BEs with literature values Experimentally measuring BEs is challenging, especially for radicals, due to their high reactivity during Temperature￾Programmed Desorption (TPD), which complicates the evalua￾tion of desorption p… view at source ↗
Figure 4
Figure 4. Figure 4: Comparison of reported BEs on water ice surfaces with our ZPE and BSSE corrected values. [PITH_FULL_IMAGE:figures/full_fig_p006_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: The fraction of binding sites with binding energies. The binding en￾ergy distribution for each species is assumed to follow a Gaussian distribution based on the four parameters noted in [PITH_FULL_IMAGE:figures/full_fig_p007_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: Time evolution of abundances obtained with the rate equation model [PITH_FULL_IMAGE:figures/full_fig_p008_6.png] view at source ↗

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This paper was first reviewed by deepseek-v4-flash on August 5, 2026.