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REVIEW 4 major objections 2 minor 97 references

Dynamics of Protonated Oxalate from Machine-Learned Simulations and Experiment: Infrared Signatures, Proton Transfer Dynamics and Tunneling Splittings

T0 review · 4 major / 2 minor · reviewed 2026-08-05 · deepseek-v4-flash

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Pith's one-line read A machine-learned potential energy surface of CCSD(T) quality reproduces the infrared spectrum of protonated oxalate, predicts a new weak band at 1666 cm^-1, and gives a 35.0 cm^-1 tunneling splitting for the H-transfer.

desk verdict Abstract describes a plausible and potentially valuable ML-PES study of protonated oxalate, but the supplied full text is an unrelated OpenFOAM CFD paper, so the submission as-is cannot be refereed. read the letter →

arxiv 2508.06419 v1 pith:YHYFARQ2 submitted 2025-08-08 physics.chem-ph

Valerii Andreichev , Silvan Käser , Erica L. Bocanegra , Madeeha Salik , Mark A. Johnson , Markus Meuwly This is my paper · ORCID
classification physics.chem-ph
keywords protonatedoxalatepotentialenergysurfacemachinelearningvibrationalspectroscopyprotontransfertunnelingsplittingringpolymerinstantonVPT2
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 aims to show that a machine-learned potential energy surface of CCSD(T) quality, tuned against new infrared measurements, captures both the vibrational framework and the proton-transfer dynamics of protonated oxalate. The key validation is that VPT2 calculations on this surface correctly identify a new low-intensity feature at 1666 $cm^{-1}$ and reproduce the measured H-transfer band around 2940 $cm^{-1}$. The paper further claims that ring-polymer instanton calculations on the same surface predict a hydrogen-transfer tunneling splitting of 35.0 $cm^{-1}$, a number that experiment can directly test. If correct, the study demonstrates that a single calibrated machine-learned surface can describe anharmonic spectroscopy, mode assignment, and quantum tunneling in a strongly hydrogen-bonded ion.

What carries the argument

The central object is a machine-learned potential energy surface (a regression fit to CCSD(T) electronic energies and forces, likely a neural network) calibrated to new infrared measurements of protonated oxalate. It supplies the potential for three separate calculations: second-order vibrational perturbation theory (VPT2), which assigns the anharmonic vibrational spectrum; molecular dynamics, which characterizes the H-transfer motion; and ring polymer instanton theory with higher-order corrections, which gives the tunneling splitting from the barrier crossing path. The surface is the single entity that ties all three predictions together.

What would settle it

Measure the high-resolution infrared spectrum of protonated oxalate (or its deuterated analogue) and locate the split transitions between the H-transfer tunneling states. If the observed splitting is significantly different from 35.0 $cm^{-1}$ (outside combined experimental and computational uncertainty), the machine-learned PES is wrong along the transfer path. Alternatively, recompute the 1666 $cm^{-1}$ band with a PES that was not calibrated against any measured oxalate frequencies; if the band disappears, the prediction was not independent.

Watch

Extended reading notes

Core claim

The central claim is that one machine-learned potential energy surface of CCSD(T) accuracy, fit with the help of new spectroscopic results, simultaneously accounts for the observed vibrational spectrum of protonated oxalate and predicts a quantitative tunneling splitting for the intramolecular H-transfer. VPT2 on this surface assigns the framework modes and the H-transfer feature, including a newly observed low-intensity band at 1666 $cm^{-1}$ that the calculations anticipated. The broad absorption from 2600 to 3200 $cm^{-1}$ is attributed to the H-transfer motion riding on a background of combination bands, with the COH bend playing the largest role. For the deuterated isotopologue, both VPT2 and m

Load-bearing premise

The agreement with experiment is treated as a validation, but the PES was 'calibrated against the results of new spectroscopic measurements'; if the bands used to judge the fits—especially the new 1666 $cm^{-1}$ feature—were included in the calibration data, then the agreement is a property of the fit rather than an independent prediction, and the 35.0 $cm^{-1}$ tunneling benchmark inherits that uncertainty.

Editorial extensions

If this is right

  • A measured tunneling splitting in protonated oxalate near 35.0 cm^-1 would confirm the machine-learned surface's fidelity along the proton-transfer path.
  • The 1666 cm^-1 band, if verified independently, provides a sensitive spectral probe of the framework's anharmonicity in strongly hydrogen-bonded anions.
  • The assignment of the 2600–3200 cm^-1 broad feature to H-transfer plus COH-bend combination bands changes how such bands are interpreted in carboxylate and oxalate systems.
  • The same fitted surface, having passed these spectral tests, can be reused for dynamics and tunneling in other isotopologues with confidence.

Reading between the lines

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

  • The tunneling splitting prediction at 35.0 cm^-1 is a benchmark unique to this PES: any competing surface for oxalate that yields a different value can be rejected by one high-resolution experiment, so the number becomes a positive test for the machine-learning training protocol.
  • If the 1666 cm^-1 band was not part of the calibration data, then its correct prediction signals that the model learned genuine physics rather than merely reproducing the fit set; if it was part of the fit, the paper's validation claim would weaken — a distinction the authors do not spell out.
  • The methodology should transfer to other ions with intramolecular hydrogen bonds, where anharmonic couplings and tunneling compete; the COH-bend's prominent role suggests that mode-specific relaxation pathways may be observable in time-resolved infrared experiments.
  • The manuscript text supplied with this submission is a fluid-dynamics paper on natural convection in vertical channels and does not match the abstract's topic; the extraction above therefore rests entirely on the abstract's statements.
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Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

4 major / 2 minor

Summary. The manuscript consists of an abstract describing a machine-learned potential energy surface (PES) for protonated oxalate at CCSD(T) quality, VPT2 and molecular dynamics infrared assignments, ring-polymer instanton tunneling splittings, and new infrared spectroscopic measurements. The abstract reports that the PES was 'calibrated against' the new spectra, that VPT2 'correctly predicted' a new 1666 cm^-1 band, and that the H-transfer tunneling splitting is predicted as Δ_H = 35.0 cm^-1. The full text supplied after the abstract, however, is an OpenFOAM CFD study of laminar natural convection in open-ended vertical channels: it contains no oxalate PES, no electronic-structure calculations, no VPT2/MD/instanton equations, no experimental infrared data, and no supplementary material. The references [1]–[35] are all CFD/heat-transfer references. Thus the manuscript's central claims are entirely unsupported by any presented evidence.

Significance. If the abstract's claims were substantiated, the work could be significant: a machine-learned PES for a small molecular ion, benchmarked against new spectroscopy and yielding a falsifiable tunneling splitting, would be a useful contribution to chemical physics. The claimed validation of a CCSD(T)-quality PES against new experimental bands, and the prediction of Δ_H = 35.0 cm^-1, would be of interest to both experimental and theoretical spectroscopists. However, the manuscript as submitted provides no derivations, data, convergence tests, or error bars. The only oxalate-specific content is the abstract; the body is an unrelated CFD study. No machine-checkable proof, reproducible code, or parameter-free derivation is present. The potential circularity from calibrating the PES against the same measurements used for validation is an additional concern that cannot be resolved from the supplied text. As a result, the significance of the reported results cannot currently be assessed.

major comments (4)
  1. [Full text (entire manuscript after the abstract)] The body of the manuscript is an OpenFOAM CFD study of natural convection in vertical channels and contains no oxalate content. There is no description of the machine-learned PES, its training set, descriptors, or fitting procedure; no VPT2, molecular dynamics, or ring-polymer instanton equations; no experimental infrared spectra; and no data tables or error bars. Every claim in the abstract — the PES calibration, the 1666 cm^-1 prediction, the 2940 cm^-1 H-transfer assignment, and Δ_H = 35.0 cm^-1 — is unsupported. This is not a local omission but a wholesale absence of the paper's subject matter.
  2. [Abstract] The abstract states that the PES was 'calibrated against the results of new spectroscopic measurements' and later cites the VPT2 calculation's 'correctly predicted' 1666 cm^-1 band and agreement with measured framework and H-transfer modes as success. No exclusion criterion is given. If the 1666 cm^-1 band or the 2600–3200 cm^-1 H-transfer region were part of the calibration data, the agreement is a property of the fit, not independent validation, and the tunneling splitting inherits the quality of the fitted surface along the transfer path. The manuscript must specify which experimental data were used in fitting and which were held out for validation.
  3. [Full text (methods and results)] No computational details are provided for the claimed VPT2, molecular dynamics, or ring-polymer instanton calculations with higher-order corrections. There are no basis sets, electronic-structure reference levels, convergence tests, or uncertainty estimates. Without these, the central prediction Δ_H = 35.0 cm^-1 is not auditable. The provided text also contains no experimental methods for the new spectroscopic measurements, so the claimed benchmark cannot be evaluated.
  4. [References [1]–[35]] The reference list is entirely devoted to natural convection and heat-transfer CFD topics (e.g., Desrayaud et al., OpenFOAM solvers). There are no citations to the oxalate literature, machine-learned PES methods, VPT2 theory, ring-polymer instanton methodology, or infrared spectroscopy of carboxylic acids. This confirms that the full text is a different manuscript and not an incomplete version of the oxalate paper.
minor comments (2)
  1. [Abstract] The phrase 'calibrated against the results of new spectroscopic measurements' should be replaced with a precise statement of the train/test split. If the target bands were excluded from fitting, that should be stated explicitly; if not, the validation claims should be reframed.
  2. [Full text (equations)] The CFD equations in the body are garbled (e.g., Eq. (2) is missing a brace, and several boundary conditions appear as corrupted encoding). While this is secondary to the main problem, it further indicates that the manuscript is not in a reviewable form.

Circularity Check

1 steps flagged · score 6.0 of 10

VPT2 'prediction' of 1666 cm^-1 band is presented as validation although the PES was calibrated against the new spectroscopic measurements; without an exclusion statement the agreement may be a property of the fit. The tunneling splitting remains a genuine forward prediction.

  1. fitted input called prediction [Abstract]
    "machine learning-based potential energy surface (PES) of CCSD(T) quality, calibrated against the results of new spectroscopic measurements. Second order vibrational perturbation calculations (VPT2) very successfully describe both the framework and H-transfer modes compared with the experiments. In particular, a new low-intensity signature at 1666 cm$^{-1}$ was correctly predicted from the VPT2 calculations."

    The PES is calibrated against the new spectroscopic measurements, and the same measurements (including the 1666 cm^-1 band, framework modes, and H-transfer region) are then used to validate VPT2. If the 1666 cm^-1 signature is part of the calibration data, the VPT2 'prediction' is not an independent test but a consequence of the fit; the abstract nowhere states that the target bands were excluded from calibration. The 35.0 cm^-1 tunneling splitting remains a forward prediction, so the circularity is partial.

full rationale

The supplied full text is an unrelated OpenFOAM CFD study and contains none of the claimed oxalate PES, VPT2/MD/instanton calculations, equations, or SI, so the derivation chain cannot be audited beyond the abstract. On the abstract's face, the validation logic is circular if the calibration set includes the target bands; the absence of an exclusion statement makes this a concrete gap rather than a remote possibility. The tunneling splitting is a genuine forward prediction from the PES and is not reduced to the fit by anything quoted, which is why the score is 6 rather than higher. No load-bearing self-citation or imported uniqueness theorem appears in the available text.

Assumptions & free parameters 2 free parameters · 4 assumptions · 0 invented entities

With the full text mismatched, this ledger is abstract-level only. The visible free parameters are the PES fitting parameters and any calibration constants tuned against the new spectra; the visible axioms are the electronic-structure reference level, the adequacy of VPT2 for a mode the abstract itself calls unstructured, the instanton approximation, and the experimental assignments. No new physical entities (particles, forces, dimensions) are announced in the abstract, so the invented-entities list is empty.

free parameters (2)
  • Machine-learned PES parameters (weights, descriptors, training set composition)
    Any neural-network potential contributing to the abstract's results is fitted to reference CCSD(T) energies; the abstract gives no details of the fitting procedure, so these parameters are unaccounted free parameters at the level of the abstract.
  • Calibration parameters against the new experimental spectra
    The abstract says the PES was 'calibrated against the results of new spectroscopic measurements'; if this calibration involves adjusting the surface to match the spectra, those adjustments are free parameters fitted to the validation data.
assumptions (4)
  • domain assumption CCSD(T)-level reference energies are accurate enough for proton transfer and tunneling in oxalate
    Invoked in 'machine learning-based potential energy surface (PES) of CCSD(T) quality'; the tunneling splitting and band shifts inherit any CCSD(T) error.
  • domain assumption VPT2 is adequate for the strongly anharmonic H-transfer mode
    The abstract assigns the unstructured 2940 cm^-1 band using second-order vibrational perturbation theory while describing the band as broad and unstructured, a regime where VPT2 normally struggles; no evidence of convergence is provided in the abstract.
  • domain assumption Ring polymer instanton with higher-order corrections gives accurate tunneling splittings
    The Δ_H = 35.0 cm^-1 prediction depends on this approximation scheme; the abstract states the corrections are used but gives no validation of the method's accuracy for this system.
  • domain assumption The experimental assignments (bands at 1666 and 2940 cm^-1) are correct
    All validation claims rest on the new measurements and their assignment; the abstract presents the measurements as ground truth.

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Cite this review

Pith. "Pith review of Dynamics of Protonated Oxalate from Machine-Learned Simulations and Experiment: Infrared Signatures, Proton Transfer Dynamics and Tunneling Splittings." pith.science (2026). https://pith.science/paper/YHYFARQ2

@misc{pith2026250806419,
  author       = {Pith},
  title        = {Pith review of: Dynamics of Protonated Oxalate from Machine-Learned Simulations and Experiment: Infrared Signatures, Proton Transfer Dynamics and Tunneling Splittings},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/YHYFARQ2}},
  note         = {Machine review of arXiv:2508.06419}
}
abstract

The infrared spectroscopy and proton transfer dynamics together with the associated tunneling splittings for H/D-transfer in oxalate are investigated using a machine learning-based potential energy surface (PES) of CCSD(T) quality, calibrated against the results of new spectroscopic measurements. Second order vibrational perturbation calculations (VPT2) very successfully describe both the framework and H-transfer modes compared with the experiments. In particular, a new low-intensity signature at 1666 cm$^{-1}$ was correctly predicted from the VPT2 calculations. An unstructured band centered at 2940 cm$^{-1}$ superimposed on a broad background extending from 2600 to 3200 cm$^{-1}$ is assigned to the H-transfer motion. The broad background involves a multitude of combination bands but a major role is played by the COH-bend. For the deuterated species, VPT2 and molecular dynamics simulations provide equally convincing assignments, in particular for the framework modes. Finally, based on the new PES the tunneling splitting for H-transfer is predicted as $\Delta_{\rm H} = 35.0$ cm$^{-1}$ from ring polymer instanton calculations using higher-order corrections. This provides an experimentally accessible benchmark to validate the computations, in particular the quality of the machine-learned PES.

Discussion (0). Continue with ORCID to comment.

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Pith tools

Reviewed August 5, 2026 · model on record in the stance chip above.