Structure–transport correlation for the diffusive tortuosity of bulk, monodisperse, random sphere packings

Khirevich, Siarhei; Höltzel, Alexandra; Daneyko, Anton; Seidel‐Morgenstern, A.; Tallarek, Ulrich

doi:10.1016/j.chroma.2011.07.066

Cited by 56 publications

(45 citation statements)

References 43 publications

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“…A packing algorithm that meets these criteria is the Jodrey-Tory algorithm 81 and its modifications. [20][21][22][23] An exemplary set of generated 2D packings of inert hard disks with a systematically adjusted degree of microstructural heterogeneity, which allows a better visualization of these effects than 3D packings of spheres, is shown in Fig. 5.…”

Section: Random Packingsmentioning

confidence: 99%

“…O = 0.95 (fast compression) or O = 0.05 (slow compression), two different packing types, O Â 0.95 and O Â 0.05, respectively, were generated. 23 The values were chosen from the ends of the possible range (0 o O r 1) to create a maximum of microstructural variety with these two Monte Carlo-packing types.…”

Section: Random Packingsmentioning

confidence: 99%

“…agreement with details followed by the algorithm, i.e., a larger displacement length (a-value) during packing generation yields a more homogeneous sphere distribution in the final packing. 22,23 The differences observed in the microstructural heterogeneity especially at higher bed porosities underline the need for an adequate description of the bed structure, if correlations with the mass transport properties of a material are established. The two parameters in Fig.…”

Section: Spatial Tessellationsmentioning

confidence: 99%

“…(B) Porosity-scaling of the normalized s(A min /A max ) D , the standard deviation of the distribution that describes the ratio between the minimum and maximum void face areas of each Delaunay tetrahedron in a tessellated packing. Reprinted from Khirevich et al 23 Copyright 2011, with permission from Elsevier. standard deviation of this distribution has a porosity-scaling (panel B) that closely mimics that of the tortuosity values for each packing type (panel A).…”

Section: Effective Diffusion Coefficientsmentioning

confidence: 99%

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Characterization of microscopic disorder in reconstructed porous materials and assessment of mass transport-relevant structural descriptors

2016

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The targeted optimization of the functional properties of porous materials includes the understanding of their transport properties and thus requires knowledge about the relationship between material synthesis, resulting in three-dimensional material morphology, and relevant transport properties. In this Perspective, we present our views and results on the characterization of microscopic disorder in functional porous materials, which are widely used today as fixed beds in adsorption, separation, and catalysis. This allows us to identify structural parameters that impact their mass transport properties and eventually their overall performance in technological operations. We address this complex topic at the following levels: (i) computer-generation of disordered packings allows the systematic investigation of the bed porosity (packing density) and degree of packing heterogeneity. These studies are complemented by the physical reconstruction of real packed and monolithic beds, which resolves the salient features of the packing process and monolith synthesis that are under the control of the experimentalist. (ii) Once reconstructed packed-bed and monolith morphologies are available, they are analysed by statistical methods to derive structural descriptors for their mass transport properties. Spatial tessellation schemes and chord length distributions are shown to be suitable for that purpose. They lead us to sensitive correlations of the degree of pore-environment heterogeneity and packing-scale disorder with the dynamics of (random) diffusion and (flow-field dependent) hydrodynamic dispersion, respectively. (iii) Direct or pore-scale numerical simulations are implemented on a highperformance computing platform to quantify the relevant transport properties of the materials. This complementary approach highlights the morphological descriptors of mass transport efficiency. They are validated by the simulations and in the future could direct the rational design of materials from their synthesis to targeted applications based on physical reconstruction.

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Section: Random Packingsmentioning

confidence: 99%

Section: Random Packingsmentioning

confidence: 99%

Section: Spatial Tessellationsmentioning

confidence: 99%

Section: Effective Diffusion Coefficientsmentioning

confidence: 99%

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Characterization of microscopic disorder in reconstructed porous materials and assessment of mass transport-relevant structural descriptors

2016

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“…Simulation methods based on such direct structural information are now well established, and have been used successfully to model flow and dispersion in diverse geometries such as fractal constructs [22], sphere packs [23–36], internal networks of porous particles [37] and more recently a silica monolith [20,38]. In a previous article [39], we presented results for the simulation of flow in a three-dimensional reconstruction of a sample block (Figure 1) of a commercially available polymeric monolith disk, the CIM TM disk from BIA Separations, using the lattice-Boltzmann (LB) methodology.…”

Section: Introductionmentioning

confidence: 99%

Modeling of dispersion in a polymeric chromatographic monolith

Koku

Maier

Schure

et al. 2012

Journal of Chromatography A

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Dispersion in a commercial polymeric monolith was simulated on a sample geometry obtained by direct imaging using high-resolution electron microscopy. A parallelized random walk algorithm, implemented using a velocity field obtained previously by the lattice-Boltzmann method, was used to model mass transfer. Both point particles and probes of finite size were studied. Dispersion simulations with point particles using periodic boundaries resulted in plate heights that varied almost linearly with flow rate, at odds with the weaker dependence suggested by the experimental observations and predicted by theory. This discrepancy resulted from the combined effect of the artificial symmetry in the velocity field and the periodic boundaries implemented to emulate macroscopic column lengths. Eliminating periodicity and simulating a single block length instead resulted in a functional dependence of plate heights on flow rate more in accord with experimental trends and theoretical predictions for random media. The lower values of the simulated plate heights than experimental ones are attributed in part to the presence of walls in real systems, an effect not modeled by the algorithm. On the other hand, analysis of transient dispersion coefficients and comparison of lateral particle positions at the entry and exit hinted at non-asymptotic behavior and a strong degree of correlation that was presumably a consequence of preferential high-velocity pathways in the raw sample block. Simulations with finite-sized probes resulted in particle trajectories that frequently terminated at narrow constrictions of the geometry. The amount of entrapment was predicted to increase monotonically with flow rate, evidently due to the relative contributions to transport of convection that carries particles to choke-points and diffusion that dislodges these entrapped particles. The overall effect is very similar to a flow-dependent entrapment phenomenon previously observed experimentally for adenovirus.

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