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arxiv: 2606.18760 · v1 · pith:YMDYLF34new · submitted 2026-06-17 · ⚛️ physics.chem-ph

Giant Nonequilibrium Fluctuations at a Reactive Surface

Hyun Tae Jung , Hyungjun Kim , Alejandro L. Garcia , Andrew J. Nonaka , John B. Bell , Ishan Srivastava , Changho Kim This is my paper

Pith reviewed 2026-06-26 19:14 UTC · model grok-4.3

classification ⚛️ physics.chem-ph
keywords nonequilibrium fluctuationsreactive surfaceheterogeneous catalysisadsorption ratestructure factorgas-surface interactionsurface coverage
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The pith

Giant fluctuations in a gas induce matching fluctuations on a reactive surface over micrometer scales.

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

The paper asks whether giant nonequilibrium fluctuations in a gas can produce corresponding fluctuations on a reactive surface in contact with the gas. Numerical simulations of a minimal heterogeneous catalytic reactor model show that such surface fluctuations do emerge, with spatial correlations extending over micrometer scales. The origin is the dependence of the adsorption rate on reactant partial pressure. As a result, the structure factor describing surface coverage mirrors the structure factor of the gas partial pressure, including its enhancement at low wave numbers and roll-off at higher wave numbers.

Core claim

Numerical simulations of a minimal heterogeneous catalytic reactor demonstrate that giant fluctuations in a gas induce corresponding fluctuations on a reactive surface, with spatial correlations extending over micrometer scales. These fluctuations originate from the dependence of the adsorption rate on the reactant partial pressure, so that the surface-coverage structure factor mirrors that of the partial pressure, exhibiting similar enhancement and roll-off behavior across wave numbers.

What carries the argument

The dependence of adsorption rate on reactant partial pressure, which transmits gas fluctuations to the surface-coverage structure factor.

Load-bearing premise

The minimal heterogeneous catalytic reactor model accurately captures the essential gas-surface interaction physics, including the functional form of the adsorption rate dependence on partial pressure, without additional effects that would suppress or alter the fluctuation propagation.

What would settle it

An experiment that measures surface coverage in a catalytic reactor and finds no spatial correlations with gas partial pressure fluctuations or correlations that decay much faster than over micrometer scales.

Figures

Figures reproduced from arXiv: 2606.18760 by Alejandro L. Garcia, Andrew J. Nonaka, Changho Kim, Hyungjun Kim, Hyun Tae Jung, Ishan Srivastava, John B. Bell.

Figure 1
Figure 1. Figure 1: FIG. 1. Schematic illustration of a gas–solid interfacial sys [PITH_FULL_IMAGE:figures/full_fig_p002_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: FIG. 2. Snapshots of the normalized surface coverage, [PITH_FULL_IMAGE:figures/full_fig_p003_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: FIG. 3. Structure factor spectra of the surface coverage [PITH_FULL_IMAGE:figures/full_fig_p003_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: FIG. 4. Surface coverage structure factor spectra for different [PITH_FULL_IMAGE:figures/full_fig_p004_4.png] view at source ↗
Figure 6
Figure 6. Figure 6: FIG. 6. Surface coverage structure factor spectra for different [PITH_FULL_IMAGE:figures/full_fig_p005_6.png] view at source ↗
read the original abstract

We investigate whether giant fluctuations in a gas can induce corresponding fluctuations on a reactive surface in contact with the gas. Numerical simulations of a minimal heterogeneous catalytic reactor demonstrate that such fluctuations indeed emerge on the surface, with spatial correlations extending over micrometer scales. These fluctuations originate from the dependence of the adsorption rate on the reactant partial pressure. As a result, the surface-coverage structure factor mirrors that of the partial pressure, exhibiting similar enhancement and roll-off behavior across wave numbers.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

0 major / 2 minor

Summary. The manuscript presents numerical simulations of a minimal heterogeneous catalytic reactor demonstrating that giant nonequilibrium fluctuations in a gas induce corresponding fluctuations on a reactive surface in contact with the gas. Spatial correlations extend over micrometer scales. These fluctuations originate from the dependence of the adsorption rate on the reactant partial pressure, such that the surface-coverage structure factor mirrors that of the partial pressure, with similar enhancement and roll-off behavior across wave numbers.

Significance. If the simulations are robust, the work provides a direct numerical demonstration, within an explicitly minimal model, of fluctuation transfer from gas-phase partial pressure to surface coverage via adsorption kinetics. This establishes a concrete mechanism for long-range spatial correlations on reactive surfaces driven by nonequilibrium gas fluctuations, which may be relevant for microscale catalysis where such effects could influence local reaction dynamics or noise characteristics. The scoping to a defined model and the mirroring structure-factor result constitute a clear, model-internal prediction.

minor comments (2)
  1. [Abstract] The abstract states the central result but provides no information on the specific model equations, rate laws, simulation parameters, grid resolution, or statistical sampling methods used to obtain the structure factors. Including these in the main text (e.g., a dedicated methods section) would allow readers to assess reproducibility and convergence.
  2. The manuscript should report error bars or uncertainty estimates on the structure-factor data, along with any convergence tests with respect to system size or simulation time, to confirm that the reported micrometer-scale correlations are not artifacts of finite sampling.

Simulated Author's Rebuttal

0 responses · 0 unresolved

We thank the referee for the positive assessment of our manuscript and the recommendation for minor revision. No major comments were provided in the report.

Circularity Check

0 steps flagged

No significant circularity; result follows from direct numerical simulation of an explicitly defined model

full rationale

The paper's central claim is obtained via numerical simulation of a minimal heterogeneous catalytic reactor model, where gas partial-pressure fluctuations propagate to surface coverage through the stated adsorption-rate dependence. This produces the mirroring structure factor as a direct consequence of the implemented physics, without parameter fitting to the target fluctuation statistics, self-definitional reductions, or load-bearing self-citations. The derivation chain is self-contained against the model's own equations and boundary conditions.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

Based solely on the abstract, the central claim rests on the assumption that the minimal reactor simulation faithfully transmits fluctuations via adsorption-rate dependence; no specific free parameters, invented entities, or additional axioms are identifiable from the given text.

axioms (1)
  • domain assumption Numerical simulation of the minimal heterogeneous catalytic reactor model is sufficient to demonstrate the fluctuation induction effect
    Invoked by the choice to use simulations of this model to show the result

pith-pipeline@v0.9.1-grok · 5614 in / 1272 out tokens · 28582 ms · 2026-06-26T19:14:30.334161+00:00 · methodology

discussion (0)

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Reference graph

Works this paper leans on

22 extracted references

  1. [1]

    Vailati and M

    A. Vailati and M. Giglio, Nature390, 262 (1997)

    1997

  2. [2]

    Brogioli, A

    D. Brogioli, A. Vailati, and M. Giglio, Phys. Rev. E61, R1 (2000)

    2000

  3. [3]

    Vailati and M

    A. Vailati and M. Giglio, Phys. Rev. E58, 4361 (1998)

    1998

  4. [4]

    J. M. Ortiz de Z´ arate and J. V. Sengers,Hydrodynamic Fluctuations in Fluids and Fluid Mixtures(Elsevier Sci- ence, 2006)

    2006

  5. [5]

    L. D. Landau and E. M. Lifschitz,Fluid Mechanics, 2nd ed. (Pergamon Press, 1987)

    1987

  6. [6]

    A. L. Garcia, J. B. Bell, A. Nonaka, I. Srivastava, D. Ladiges, and C. Kim, SIAM Rev. To appear, arXiv:2406.12157

    arXiv

  7. [7]

    Donev, J

    A. Donev, J. B. Bell, A. de la Fuente, and A. L. Garcia, Phys. Rev. Lett.106, 204501 (2011)

    2011

  8. [8]

    C. J. Takacs, A. Vailati, R. Cerbino, S. Mazzoni, M. Giglio, and D. S. Cannell, Phys. Rev. Lett.106, 244502 (2011)

    2011

  9. [9]

    J. M. Ortiz de Z´ arate, T. R. Kirkpatrick, and J. V. Sen- gers, Eur. Phys. J. E38, 99 (2015)

    2015

  10. [10]

    Croccolo, J

    F. Croccolo, J. M. Ortiz de Z´ arate, and J. V. Sengers, Eur. Phys. J. E39, 125 (2016)

    2016

  11. [11]

    Vailati, H

    A. Vailati, H. Bataller, M. M. Bou-Ali, M. Carpineti, R. Cerbino, F. Croccolo, S. U. Egelhaaf, F. Gi- avazzi, C. Giraudet, G. Guevara-Carrion, D. Horv´ ath, W. K¨ ohler, A. Mialdun, J. Porter, K. Schwarzenberger, V. Shevtsova, and A. D. Wit, npj Microgravity9, 1 (2023)

    2023

  12. [12]

    C. Kim, A. Nonaka, J. B. Bell, A. L. Garcia, and A. Donev, J. Chem. Phys.149, 084113 (2018)

    2018

  13. [13]

    H. T. Jung, H. Kim, A. L. Garcia, A. J. Nonaka, J. B. 6 Bell, I. Srivastava, and C. Kim, J. Chem. Phys.164, 094103 (2026)

    2026

  14. [14]

    Srivastava, D

    I. Srivastava, D. R. Ladiges, A. J. Nonaka, A. L. Garcia, and J. B. Bell, Phys. Rev. E107, 015305 (2023)

    2023

  15. [15]

    J. M. Ortiz de Z´ arate and L. M. Redondo, Eur. Phys. J. B21, 135 (2001)

    2001

  16. [16]

    FHDeX, https://github.com/AMReX-FHD/FHDeX.git

  17. [17]

    C. Kim, A. Nonaka, J. B. Bell, A. L. Garcia, and A. Donev, J. Chem. Phys.146, 124110 (2017). End Matter Numerical Structure Factors—In this work, we nu- merically compute two static structure factor spectra, Sθ(k⊥) andS (surf) Y (k⊥), characterizing the spatial cor- relations of fluctuations occurring at or near the reactive surface. These spectra are obt...

    2017

  18. [18]

    (S15) into Eq

    Dynamic Structure FactorS Y (ω,k⊥,z,z ′)and Static Structure FactorS Y (k⊥,z,z ′) Substituting Eq. (S15) into Eq. (S1) and using Eq. (S17), the dynamic structure factor SY (ω,k⊥,z,z ′) is given by SY (ω,k⊥,z,z ′) = (630L3)2⟨G(ω,k⊥)G∗(ω,k⊥)⟩/(2π)3 [ωL2(k2 ⊥L2 + 12)]2 + [ν(k4 ⊥L4 + 24k2 ⊥L2 + 504)]2|∇Y|2 × ∞∑ N=1 ∞∑ M=1 WN cos ( (2N−1)πz 2L ) iω+D ( (2N−1)2...

  19. [19]

    Bulk Structure FactorS (bulk) Y (k⊥) From the static structure factorS Y (k⊥,z,z ′), the scattering intensityS (bulk) Y (k⊥,k∥) can be computed as [1] S(bulk) Y (k⊥,k∥) = 1 L ∫ L 0 ∫ L 0 e−ik∥(z−z′)SY (k⊥,z,z ′)dzdz′ (S21) and, in the limitk ∥→0, we obtain S(bulk) Y (k⊥) =kBT|∇Y|2 ρD 40320k2 ⊥L6 π2 ∞∑ N=1 ∞∑ M=1 1 ((2N−1)2 + (2M−1)2)π2 + 8k2 ⊥L2 ×(−1)N+M ...

  20. [20]

    Cross-sectional Structure FactorS (zℓ) Y (k⊥) While the bulk structure factor corresponds to an average over the entire system, the cross-sectional structure factor requires resolving the intensity within individual slices 11 of thickness ∆z. From the static structure factorS Y (k⊥,z,z ′), the scattering intensity S(zℓ) Y (k⊥,k∥) can be computed as S(zℓ) ...

  21. [21]

    Hence, S(surf) Y ≈S(z1) Y,eq +S (z1) Y + ∆S (z1) Y .(S30)

    Structure Factor Immediately above the Surface,S (surf) Y (k⊥) The structure factor immediately above the planez= 0, denoted byS (surf) Y (k⊥) in the main text, is obtained from the cross-sectional structure factor withℓ= 1. Hence, S(surf) Y ≈S(z1) Y,eq +S (z1) Y + ∆S (z1) Y .(S30)

  22. [22]

    J. M. Ortiz de Z´ arate and L. M. Redondo, Eur. Phys. J. B21, 135 (2001). 13 21

    2001