Diffusiophoresis in a Taylor-dispersing solute

E., Migacz, Robben; Ault, Jesse T.

doi:10.1103/physrevfluids.7.034202

Cited by 12 publications

(25 citation statements)

References 41 publications

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“…It would be straightforward to include features of their model such as a colloidal reaction term, an externally driven flow, and a cylindrical channel geometry into our model. Migacz & Ault (2022) also present a Taylor dispersion model of diffusiophoretic colloids with an externally driven flow field; their focus is on a narrow 2-D channel for which they neglect the diffusioosmotic wall slip. It would be straightforward to include in our model the zeta-potential dependence on the solute concentration featured in their model, although to incorporate their characterization of early-time dynamics requires further research.…”

Section: Derivation Of a 1-d Cross-sectionally Averaged Concentration...mentioning

confidence: 99%

“…2020, 2021; Gupta et al. 2020 b ; Migacz & Ault 2022). However, these studies assume a model configuration where the flow due to sidewalls is not considered.…”

Section: Introductionmentioning

confidence: 99%

“…2016; Chu et al. 2021; Migacz & Ault 2022). Still, our two-dimensional (2-D) model yielded a lower quantitative dispersion value than experiments and thus the agreement between the model and experiments remained qualitative.…”

Section: Introductionmentioning

confidence: 99%

“…In our previous article, we demonstrated that particle motion due to diffusiophoresis and a diffusioosmotic-slip-driven flow field that neglects the smallest dimension of the pore does predict a non-zero dispersion of colloids (Alessio et al 2021). Physically, diffusioosmosis along the sidewalls creates a flow structure that stretches the particle distribution along the pore, and generates an apparent motion of particles that is analogous to Taylor dispersion (Taylor 1953;Aris 1956;Doshi, Daiya & Gill 1978;Stone & Brenner 1999;Aminian et al 2016;Chu et al 2021;Migacz & Ault 2022). Still, our two-dimensional (2-D) model yielded a lower quantitative dispersion value than experiments and thus the agreement between the model and experiments remained qualitative.…”

Section: Introductionmentioning

confidence: 99%

“…To enable widespread use of diffusiophoresis in lab-on-a-chip applications such as energy storage and desalination devices (Bone, Steinrück & Toney 2020;Gupta et al 2020a;Gupta, Zuk & Stone 2020c), particle separation (Lee et al 2018;Seo et al 2020;Shin 2020), colloidal focusing and delivery (Banerjee et al 2016;Shi et al 2016;Gandhi et al 2020), ion-exchange membranes (Florea et al 2014), zeta potential measurement (Shin et al 2017) and macromolecule transport in biological systems (Bruno et al 2018;Hartman, Božič & Derganc 2018;Yang et al 2018), understanding and quantifying dispersion is crucial. Recently, studies have modelled the dispersion of a patch of particles that spread due to diffusiophoresis (Raynal & Volk 2019;Chu et al 2020Chu et al , 2021Gupta et al 2020b;Migacz & Ault 2022). However, these studies assume a model configuration where the flow due to sidewalls is not considered.…”

Section: Introductionmentioning

confidence: 99%

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Diffusioosmosis-driven dispersion of colloids: a Taylor dispersion analysis with experimental validation

et al. 2022

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Diffusiophoresis refers to the movement of colloidal particles in the presence of a concentration gradient of a solute and enables directed motion of colloidal particles in geometries that are inaccessible, such as dead-end pores, without imposing an external field. Previous experimental reports on dead-end pore geometries show that, even in the absence of mean flow, colloidal particles moving through diffusiophoresis exhibit significant dispersion. Existing models of diffusiophoresis are not able to predict the dispersion and thus the comparison between the experiments and the models is largely qualitative. To address these quantitative differences between the experiments and models, we derive an effective one-dimensional equation, similar to a Taylor dispersion analysis, that accounts for the dispersion created by diffusioosmotic flow from the channel sidewalls. We derive the effective dispersion coefficient and validate our results by comparing them with direct numerical simulations. We also compare our model with experiments and obtain quantitative agreement for a wide range of colloidal particle sizes. Our analysis reveals two important conclusions. First, in the absence of mean flow, dispersion is driven by the flow created by diffusioosmotic wall slip such that spreading can be reduced by decreasing the channel wall diffusioosmotic mobility. Second, the model can explain the spreading of colloids in a dead-end pore for a wide range of particle sizes. We note that, while the analysis presented here focuses on a dead-end pore geometry with no mean flow, our theoretical framework is general and can be adapted to other geometries and other background flows.

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Section: Derivation Of a 1-d Cross-sectionally Averaged Concentration...mentioning

confidence: 99%

“…2020, 2021; Gupta et al. 2020 b ; Migacz & Ault 2022). However, these studies assume a model configuration where the flow due to sidewalls is not considered.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Diffusioosmosis-driven dispersion of colloids: a Taylor dispersion analysis with experimental validation

et al. 2022

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The role of variable zeta potential on diffusiophoretic and diffusioosmotic transport

Lee

Ault

2023

Colloids and Surfaces A: Physicochemical and Engineering Aspect

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Diffusioosmotic dispersion of solute in a long narrow channel

Teng,

Rallabandi,

Ault

2023

J. Fluid Mech.

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Solute–surface interactions have garnered considerable interest in recent years as a novel control mechanism for driving unique fluid dynamics and particle transport with potential applications in fields such as biomedicine, the development of microfluidic devices and enhanced oil recovery. In this study, we will discuss dispersion induced by the diffusioosmotic motion near a charged wall in the presence of a solute concentration gradient. Here, we introduce a plug of salt with a Gaussian distribution at the centre of a channel with no background flow. As the solute diffuses, the concentration gradient drives a diffusioosmotic slip flow at the walls, which results in a recirculating flow in the channel; this, in turn, drives an advective flux of the solute concentration. This effect leads to cross-stream diffusion of the solute, altering the effective diffusivity of the solute as it diffuses along the channel. We derive theoretical predictions for the solute dynamics using a multiple-time-scale analysis to quantify the dispersion driven by the solute–surface interactions. Furthermore, we derive a cross-sectionally averaged concentration equation with an effective diffusivity analogous to that from Taylor dispersion. In addition, we use numerical simulations to validate our theoretical predictions.

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Diffusiophoresis in a Taylor-dispersing solute

Cited by 12 publications

References 41 publications

Diffusioosmosis-driven dispersion of colloids: a Taylor dispersion analysis with experimental validation

Diffusioosmosis-driven dispersion of colloids: a Taylor dispersion analysis with experimental validation

The role of variable zeta potential on diffusiophoretic and diffusioosmotic transport

Diffusioosmotic dispersion of solute in a long narrow channel

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