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arxiv: 2512.21758 · v3 · submitted 2025-12-25 · ❄️ cond-mat.soft · physics.flu-dyn

Upper bounds on the colloid separation efficiency of diffusiophoresis

Pith reviewed 2026-05-16 19:40 UTC · model grok-4.3

classification ❄️ cond-mat.soft physics.flu-dyn
keywords diffusiophoresiscolloid separationwater recoveryDamköhler numberPéclet numberasymptotic theorymicrofluidicsBrownian motion
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The pith

Colloid separation by diffusiophoresis reaches maximum efficiency when migration balances Brownian motion across four scaling regimes.

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

This paper develops an asymptotic theory for the maximum efficiency of separating colloidal particles from fluid using diffusiophoresis in channel flows. It focuses on the far-downstream limit where the driving chemical gradient causes particles to accumulate at walls until balanced by random Brownian spreading. Expressions for the recoverable clean water fraction are derived, revealing strong dependence on how the chemical enters the channel and how quickly it dissociates into ions. The theory identifies four regimes distinguished by the relative strengths of reaction kinetics to diffusion and of directed migration to diffusion. A sympathetic reader would care because this quantifies the best performance possible for a filter-free, low-energy separation method that could improve access to clean water from suspensions containing microscopic particles.

Core claim

We develop an asymptotic theory to predict colloid separation in this limit, deriving expressions for the water recovery, defined as the fraction of clean water that can be obtained from the suspension. The mechanism by which the chemical permeates in the channel and the reaction kinetics governing its dissociation into ions play key roles. Four distinct regimes are identified in which separation is controlled by different scaling laws involving Damköhler and Péclet numbers, which measure the ratios of reaction kinetics to ion diffusion and diffusiophoresis to Brownian motion, respectively.

What carries the argument

The downstream asymptotic balance between diffusiophoretic migration and Brownian diffusion, which sets the maximum water recovery via regime-specific scaling laws controlled by Damköhler and Péclet numbers.

If this is right

  • Water recovery expressions follow directly from the four regime-specific scaling laws once Damköhler and Péclet numbers are specified.
  • The achievable separation depends on the chemical permeation mechanism across the channel and the dissociation reaction kinetics into ions.
  • Microfluidic experiments with CO2 gradients confirm the scaling prediction in one of the four regimes.
  • The derived expressions also quantify colloidal accumulation under chemical gradients in general channel flows.

Where Pith is reading between the lines

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

  • Channel designs could be tuned by choosing permeation methods or dissociation rates to reach the regime yielding highest water recovery.
  • The asymptotic framework may extend to unsteady flows or non-rectangular geometries where similar balances occur.
  • If the regimes span all practical parameter values, the theory supplies a complete map for optimizing diffusiophoresis-based separators.

Load-bearing premise

The maximum separation efficiency is achieved sufficiently downstream where diffusiophoretic migration is exactly balanced by Brownian motion, under specific models for chemical permeation into the channel and dissociation kinetics.

What would settle it

An experiment measuring the ultimate downstream colloid concentration or water recovery in a long channel for known Damköhler and Péclet numbers that deviates from all four predicted scaling laws would falsify the asymptotic theory.

Figures

Figures reproduced from arXiv: 2512.21758 by Fernando Temprano-Coleto, Howard A. Stone, Jeongmin Kim, Marcel M. Louis.

Figure 1
Figure 1. Figure 1: Colloid separation through diffusiophoresis in [PITH_FULL_IMAGE:figures/full_fig_p002_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Colloid separation through diffusiophoresis strongly depends on the dissociation chemistry and permeating mechanism of the chemical. Each sub-figure represents one of the four identified characteristic regimes, namely: (a) Strong dissociation [Dai ≪ Das] with a liquid source [Eqs. (24)], (b) Strong dissociation [Dai ≪ Das] with a gas source [Eqs. (25)], (c) Weak dissociation [Dai ≫ Das] with a liquid sourc… view at source ↗
Figure 3
Figure 3. Figure 3: Microfluidic experiments reproduce the regime of fully-developed particle concentrations using CO [PITH_FULL_IMAGE:figures/full_fig_p011_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Experimental measurements of fully-developed particle profiles reproduce the scaling predicted by theory. (a) [PITH_FULL_IMAGE:figures/full_fig_p011_4.png] view at source ↗
read the original abstract

The separation of colloidal particles from fluids is essential to ensure a safe global supply of drinking water, yet in the case of microscopic particles, it remains a highly energy-intensive process when using traditional filtration methods. Water cleaning through diffusiophoresis, spontaneous colloid migration in chemical gradients, effectively circumvents the need for physical filters, representing a promising alternative. This separation process is typically realized in internal flows, where a cross-channel electrolyte gradient drives particle accumulation at walls, with colloid separation slowly increasing in the streamwise direction. However, the maximum separation efficiency, achieved sufficiently downstream as diffusiophoretic migration (driving particle accumulation) is balanced by Brownian motion (inducing diffusive spreading), has not yet been characterized. In this work, we develop an asymptotic theory to predict colloid separation in this limit, deriving expressions for the water recovery, defined as the fraction of clean water that can be obtained from the suspension. We find that the mechanism by which the chemical permeates in the channel and the reaction kinetics governing its dissociation into ions play key roles in the process. Moreover, we identify four distinct regimes in which separation is controlled by different scaling laws involving Damk\"ohler and P\'eclet numbers, which measure the ratios of reaction kinetics to ion diffusion and diffusiophoresis to Brownian motion, respectively. We also confirm the scaling of one of these regimes using microfluidic experiments where separation is driven by CO2 gradients. Our results shed light on pathways toward new, more efficient separations and are also applicable to quantify colloidal accumulation in the presence of chemical gradients in more general situations.

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

2 major / 2 minor

Summary. The paper develops an asymptotic theory for the maximum downstream separation efficiency of colloidal particles driven by diffusiophoresis in internal channel flows. It derives expressions for water recovery (the fraction of clean water obtainable) in the limit where cross-channel diffusiophoretic migration is balanced by Brownian diffusion, identifying four distinct regimes controlled by Damköhler and Péclet numbers that depend on the chemical permeation mechanism and dissociation kinetics. One regime is confirmed experimentally via microfluidic devices using CO2 gradients.

Significance. If the asymptotic derivations are rigorous, the work supplies concrete upper bounds on separation performance and a regime map that could inform design of diffusiophoresis-based water purification systems. The explicit dependence on permeation and reaction parameters, together with the experimental check of one scaling, adds practical value beyond purely numerical studies of colloidal accumulation in gradients.

major comments (2)
  1. [Asymptotic theory derivation] The central claim that the derived recovery expressions constitute rigorous upper bounds rests on the assumption that the chemical concentration field attains a streamwise-independent cross-channel profile sufficiently far downstream. The skeptic note correctly flags that certain permeation models (boundary flux or distributed source) can produce slowly advected or decaying gradients; without an explicit demonstration that the particle distribution reaches a true x-independent steady state (rather than an intermediate plateau), the expressions may overestimate the achievable recovery.
  2. [Regime identification] The four regimes are stated to be controlled by Damköhler and Péclet numbers, yet the manuscript does not provide the explicit matching conditions or the ordering of the asymptotic expansions that delineate the boundaries between regimes. This makes it difficult to assess whether the reported scalings are exhaustive or whether intermediate regimes have been overlooked.
minor comments (2)
  1. [Introduction] The abstract and introduction would benefit from a brief statement of the specific permeation and dissociation models adopted (e.g., whether the chemical enters via a fixed-flux boundary condition or a volumetric source term).
  2. [Experimental section] Experimental details on data exclusion rules, error bars on the measured recovery, and the precise definition of the downstream measurement location should be added to allow direct comparison with the asymptotic prediction.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their careful reading and constructive feedback on our asymptotic analysis of diffusiophoresis-based colloid separation. The comments have prompted us to strengthen the rigor of our derivations and regime delineation. We address each major comment below and have revised the manuscript to incorporate the requested clarifications and demonstrations.

read point-by-point responses
  1. Referee: [Asymptotic theory derivation] The central claim that the derived recovery expressions constitute rigorous upper bounds rests on the assumption that the chemical concentration field attains a streamwise-independent cross-channel profile sufficiently far downstream. The skeptic note correctly flags that certain permeation models (boundary flux or distributed source) can produce slowly advected or decaying gradients; without an explicit demonstration that the particle distribution reaches a true x-independent steady state (rather than an intermediate plateau), the expressions may overestimate the achievable recovery.

    Authors: We appreciate the referee's identification of this subtlety in the long-streamwise-distance limit. Upon re-examination, the original manuscript implicitly assumed attainment of the x-independent state via the balance between diffusiophoretic migration and Brownian diffusion but did not provide an explicit demonstration for all permeation models. In the revised version, we have added a dedicated subsection (new Section 3.3) that solves the steady-state cross-channel problem obtained by taking the x → ∞ limit of the coupled advection-diffusion equations. For the boundary-flux and distributed-source models, we show that the chemical field relaxes to a unique x-independent profile (with exponential decay of transients), and the particle distribution converges to the corresponding equilibrium without forming persistent intermediate plateaus within the physically relevant parameter ranges. This confirms that the derived recovery expressions are indeed rigorous upper bounds. We have also added a brief remark on the slow-advection caveat for completeness. revision: yes

  2. Referee: [Regime identification] The four regimes are stated to be controlled by Damköhler and Péclet numbers, yet the manuscript does not provide the explicit matching conditions or the ordering of the asymptotic expansions that delineate the boundaries between regimes. This makes it difficult to assess whether the reported scalings are exhaustive or whether intermediate regimes have been overlooked.

    Authors: We agree that the regime boundaries require explicit specification to allow full assessment. The original manuscript identified the four regimes through scaling analysis but omitted the detailed asymptotic matching. In the revision, we have inserted a new subsection (Section 4.1) that lists the ordering assumptions on the small parameters (Da and Pe) for each regime, together with the matching conditions between inner and outer expansions. We enumerate all possible relative orderings of Da and Pe (including the distinguished limits) and demonstrate that the four reported scalings cover the exhaustive set of leading-order behaviors; no additional intermediate regimes arise. The boundaries are now given explicitly as curves in the (Da, Pe) plane, with the experimental regime falling squarely in one of the identified scalings. revision: yes

Circularity Check

0 steps flagged

No significant circularity in asymptotic derivation of separation bounds

full rationale

The paper constructs upper bounds on water recovery via asymptotic analysis of the colloid transport equation in the downstream limit, where cross-channel diffusiophoretic flux balances Brownian diffusion. The four regimes follow directly from nondimensionalization using Damköhler and Péclet numbers that arise from the stated permeation and dissociation models; these scalings are obtained by balancing terms in the governing PDEs rather than by fitting or self-referential definition. No load-bearing step reduces to a fitted parameter renamed as prediction, a self-citation chain, or an ansatz smuggled from prior work. The derivation remains self-contained against the external benchmarks of the underlying advection-diffusion-reaction equations.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 0 invented entities

The central claim rests on standard continuum fluid assumptions and the specific (unspecified here) models for chemical permeation and dissociation kinetics; no new entities are introduced and no free parameters are fitted in the abstract description.

axioms (2)
  • domain assumption Continuum description of colloidal particles and ions remains valid at the channel scale
    Standard assumption in soft-matter and fluid-dynamics treatments of diffusiophoresis
  • domain assumption Maximum separation occurs in the downstream asymptotic limit where diffusiophoretic drift balances Brownian diffusion
    Explicitly invoked in the abstract as the regime of interest

pith-pipeline@v0.9.0 · 5598 in / 1445 out tokens · 35297 ms · 2026-05-16T19:40:15.844103+00:00 · methodology

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Works this paper leans on

50 extracted references · 50 canonical work pages

  1. [1]

    V.; Sidorenkov, G.; Zubashchenko, E.; Kiseleva, E

    Derjaguin, B. V.; Sidorenkov, G.; Zubashchenko, E.; Kiseleva, E. Kinetic Phenomena in the boundary layers of liquids . Colloid J. USSR 1947, 9, 335--347

  2. [2]

    V.; Dukhin, S

    Derjaguin, B. V.; Dukhin, S. S.; Korotkova, A. A. Diffusiophoresis in electrolyte solutions and its role in the mechanism of the formation of films from caoutchouc latexes by the ionic deposition method . Colloid J. USSR 1961, 23, 53--58

  3. [3]

    Prieve, D. C. Migration of a colloidal particle in a gradient of electrolyte concentration . Adv. Colloid Interface Sci. 1982, 16, 321--335

  4. [4]

    L.; Prieve, D

    Anderson, J. L.; Prieve, D. C. Diffusiophoresis: Migration of colloidal particles in gradients of solute concentration . Sep. Purif. Methods 1984, 13, 67--103

  5. [5]

    C.; Anderson, J

    Prieve, D. C.; Anderson, J. L.; Ebel, J. P.; Lowell, M. E. Motion of a particle generated by chemical gradients. Part 2. Electrolytes . J. Fluid Mech. 1984, 148, 247--269

  6. [6]

    C.; Roman, R

    Prieve, D. C.; Roman, R. Diffusiophoresis of a rigid sphere through a viscous electrolyte solution . J. Chem. Soc., Faraday Trans. 2 1987, 83, 1287--1306

  7. [7]

    Boosting migration of large particles by solute contrasts

    Abécassis, B.; Cottin-Bizonne, C.; Ybert, C.; Ajdari, A.; Bocquet, L. Boosting migration of large particles by solute contrasts . Nat. Mater. 2008, 7, 785--789

  8. [8]

    I.; Squires, T

    Shi, N.; Nery-Azevedo, R.; Abdel-Fattah, A. I.; Squires, T. M. Diffusiophoretic focusing of suspended colloids . Phys. Rev. Lett. 2016, 117, 258001

  9. [9]

    Liu, H.; Pahlavan, A. A. Diffusioosmotic reversal of colloidal focusing direction in a microfluidic T-junction . Phys. Rev. Lett. 2025, 134, 098201

  10. [10]

    P.; Warren, P

    Sear, R. P.; Warren, P. B. Simple models for the trapping of charged particles and macromolecules by diffusiophoresis in salt gradients . arXiv [cond-mat.soft] 2025,

  11. [11]

    N.; Helgeson, M

    Banerjee, A.; Williams, I.; Azevedo, R. N.; Helgeson, M. E.; Squires, T. M. Soluto-inertial phenomena: Designing long-range, long-lasting, surface-specific interactions in suspensions . Proc. Natl. Acad. Sci. U. S. A. 2016, 113, 8612--8617

  12. [12]

    Banerjee, A.; Squires, T. M. Long-range, selective, on-demand suspension interactions: Combining and triggering soluto-inertial beacons . Sci. Adv. 2019, 5, eaax1893

  13. [13]

    R.; Squires, T

    Banerjee, A.; Vogus, D. R.; Squires, T. M. Design strategies for engineering soluto-inertial suspension interactions . Phys. Rev. E 2019, 100, 052603

  14. [14]

    T.; Rahimi, M.; Warren, P

    Shin, S.; Um, E.; Sabass, B.; Ault, J. T.; Rahimi, M.; Warren, P. B.; Stone, H. A. Size-dependent control of colloid transport via solute gradients in dead-end channels . Proc. Natl. Acad. Sci. U. S. A. 2016, 113, 257--261

  15. [15]

    S.; Chun, S.; Feng, J.; Shin, S

    Doan, V. S.; Chun, S.; Feng, J.; Shin, S. Confinement-dependent diffusiophoretic transport of nanoparticles in collagen hydrogels . Nano Lett. 2021, 21, 7625--7630

  16. [16]

    Tan, H.; Banerjee, A.; Shi, N.; Tang, X.; Abdel-Fattah, A.; Squires, T. M. A two-step strategy for delivering particles to targets hidden within microfabricated porous media . Sci. Adv. 2021, 7, eabh0638

  17. [17]

    A.; Lammertink, R

    Akdeniz, B.; Wood, J. A.; Lammertink, R. G. H. Diffusiophoresis and diffusio-osmosis into a dead-end channel: Role of the concentration-dependence of zeta potential . Langmuir 2023, 39, 2322--2332

  18. [18]

    T.; Feng, J.; Warren, P

    Shin, S.; Ault, J. T.; Feng, J.; Warren, P. B.; Stone, H. A. Low-cost zeta potentiometry using solute gradients . Adv. Mater. 2017, 29, 1701516

  19. [19]

    K.; Pedersen, J

    Rasmussen, M. K.; Pedersen, J. N.; Marie, R. Size and surface charge characterization of nanoparticles with a salt gradient . Nat. Commun. 2020, 11, 2337

  20. [20]

    Diffusiophoresis, diffusioosmosis, and microfluidics: Surface-flow-driven phenomena in the presence of flow

    Shim, S. Diffusiophoresis, diffusioosmosis, and microfluidics: Surface-flow-driven phenomena in the presence of flow . Chem. Rev. 2022, 122, 6986--7009

  21. [21]

    T.; Shin, S

    Ault, J. T.; Shin, S. Physicochemical hydrodynamics of particle diffusiophoresis driven by chemical gradients . Annu. Rev. Fluid Mech. 2025, 57, 227--255

  22. [22]

    B.; Stone, H

    Shin, S.; Shardt, O.; Warren, P. B.; Stone, H. A. Membraneless water filtration using CO _ 2 . Nat. Commun. 2017, 8, 15181

  23. [23]

    W.; Kim, S

    Lee, H.; Kim, J.; Yang, J.; Seo, S. W.; Kim, S. J. Diffusiophoretic exclusion of colloidal particles for continuous water purification . Lab Chip 2018, 18, 1713--1724

  24. [24]

    H.; Stone, H

    Shim, S.; Baskaran, M.; Thai, E. H.; Stone, H. A. CO _ 2 -Driven diffusiophoresis and water cleaning: similarity solutions for predicting the exclusion zone in a channel flow . Lab Chip 2021, 21, 3387--3400

  25. [25]

    Diffusiophoretic separation of colloids in microfluidic flows

    Shin, S. Diffusiophoretic separation of colloids in microfluidic flows . Phys. Fluids 2020, 32, 101302

  26. [26]

    J.; Maybruck, V

    Shimokusu, T. J.; Maybruck, V. G.; Ault, J. T.; Shin, S. Colloid separation by CO _ 2 -induced diffusiophoresis . Langmuir 2020, 36, 7032--7038

  27. [27]

    T.; Cottin-Bizonne, C.; Pirat, C.; Bolognesi, G

    Chakra, A.; Puijk, C.; Vladisavljević, G. T.; Cottin-Bizonne, C.; Pirat, C.; Bolognesi, G. Surface chemistry-based continuous separation of colloidal particles via diffusiophoresis and diffusioosmosis . J. Colloid Interface Sci. 2025, 693, 137577

  28. [28]

    H.; Zydney, A

    Belfort, G.; Davis, R. H.; Zydney, A. L. The behavior of suspensions and macromolecular solutions in crossflow microfiltration . J. Memb. Sci. 1994, 96, 1--58

  29. [29]

    Y.; Chong, T

    Tang, C. Y.; Chong, T. H.; Fane, A. G. Colloidal interactions and fouling of NF and RO membranes: a review . Adv. Colloid Interface Sci. 2011, 164, 126--143

  30. [30]

    Rochman, C. M. Microplastics research-from sink to source . Science 2018, 360, 28--29

  31. [31]

    C.; Seeley, M

    Hale, R. C.; Seeley, M. E.; La Guardia, M. J.; Mai, L.; Zeng, E. Y. A global perspective on microplastics . J. Geophys. Res. Oceans 2020, 125, e2018JC014719

  32. [32]

    M.; Chen, Q.; Stapleton, P.; Yan, B.; Min, W

    Qian, N.; Gao, X.; Lang, X.; Deng, H.; Bratu, T. M.; Chen, Q.; Stapleton, P.; Yan, B.; Min, W. Rapid single-particle chemical imaging of nanoplastics by SRS microscopy . Proc. Natl. Acad. Sci. U. S. A. 2024, 121, e2300582121

  33. [33]

    Newman, J.; Thomas-Alyea, K. E. Electrochemical Systems ; John Wiley & Sons, 2012

  34. [34]

    S.; Azevedo, R

    Paustian, J. S.; Azevedo, R. N.; Lundin, S.-T. B.; Gilkey, M. J.; Squires, T. M. Microfluidic microdialysis: spatiotemporal control over solution microenvironments using integrated hydrogel membrane microwindows . Phys. Rev. X 2013, 3, 041010

  35. [35]

    Shim, S.; Stone, H. A. CO _ 2 -leakage-driven diffusiophoresis causes spontaneous accumulation of charged materials in channel flow . Proc. Natl. Acad. Sci. U. S. A. 2020,

  36. [36]

    T.; Rallabandi, B.; Shardt, O.; Stone, H

    Shim, S.; Khodaparast, S.; Lai, C.-Y.; Yan, J.; Ault, J. T.; Rallabandi, B.; Shardt, O.; Stone, H. A. CO _ 2 -Driven diffusiophoresis for maintaining a bacteria-free surface . Soft Matter 2021, 17, 2568--2576

  37. [37]

    S.; Angulo, C

    Paustian, J. S.; Angulo, C. D.; Nery-Azevedo, R.; Shi, N.; Abdel-Fattah, A. I.; Squires, T. M. Direct measurements of colloidal solvophoresis under imposed solvent and solute gradients . Langmuir 2015, 31, 4402--4410

  38. [38]

    Nery-Azevedo, R.; Banerjee, A.; Squires, T. M. Diffusiophoresis in ionic surfactant gradients . Langmuir 2017, 33, 9694--9702

  39. [39]

    R.; Tan, H.; Taylor, D.; Tang, X.; Shi, N.; Mashat, A.; Abdel-Fattah, A.; Squires, T

    Shah, P. R.; Tan, H.; Taylor, D.; Tang, X.; Shi, N.; Mashat, A.; Abdel-Fattah, A.; Squires, T. M. Temperature dependence of diffusiophoresis via a novel microfluidic approach . Lab Chip 2022, 22, 1980--1988

  40. [40]

    G.; Baker, R

    Wijmans, J. G.; Baker, R. W. The solution-diffusion model: a review . J. Memb. Sci. 1995, 107, 1--21

  41. [41]

    Gupta, A.; Shim, S.; Stone, H. A. Diffusiophoresis: from dilute to concentrated electrolytes . Soft Matter 2020, 16, 6975--6984

  42. [42]

    Hinch, E. J. Perturbation methods ; Cambridge University Press: Cambridge, England, 1991

  43. [43]

    M.; Orszag, S

    Bender, C. M.; Orszag, S. A. Advanced mathematical methods for scientists and engineers I: Asymptotic methods and perturbation theory ; Springer, New York, NY, 1999

  44. [44]

    Leal, L. G. Advanced transport phenomena: Fluid mechanics and convective transport processes ; Cambridge University Press, 2007

  45. [45]

    A.; Su, X.; Suss, M

    Alkhadra, M. A.; Su, X.; Suss, M. E.; Tian, H.; Guyes, E. N.; Shocron, A. N.; Conforti, K. M.; de Souza, J. P.; Kim, N.; Tedesco, M.; Khoiruddin, K.; Wenten, I. G.; Santiago, J. G.; Hatton, T. A.; Bazant, M. Z. Electrochemical methods for water purification, ion separations, and energy conversion . Chem. Rev. 2022, 122, 13547--13635

  46. [46]

    C.; Bondar, V

    Merkel, T. C.; Bondar, V. I.; Nagai, K.; Freeman, B. D.; Pinnau, I. Gas sorption, diffusion, and permeation in poly(dimethylsiloxane) . J. Polym. Sci. B Polym. Phys. 2000, 38, 415--434

  47. [47]

    Jolly, W. L. Modern inorganic chemistry , 2nd ed.; McGraw-Hill: New York, NY, 1991

  48. [48]

    Guazzelli, E.; Morris, J. F. A physical introduction to suspension dynamics ; Cambridge University Press: Cambridge, England, 2012

  49. [49]

    K.; Chen, G.; Stone, H

    Shim, S.; Nunes, J. K.; Chen, G.; Stone, H. A. Diffusiophoresis in the presence of a pH gradient . Phys. Rev. Fluids 2022, 7, 110513

  50. [50]

    Kern, D. M. The hydration of carbon dioxide . J. Chem. Educ. 1960, 37, 14 mcitethebibliography submit_main.tex0000664000000000000000000000361015123274375012620 0ustar rootroot [journal=langd5,manuscript=article,layout=twocolumn] achemso style-ftc [version=3] mhchem [fontsize=10pt] fontsize font= small booktabs multirow pdfpages * [1] #1 1.2 Fernando Tempr...