No abstract

No abstract

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.

We present a fast, nondestructive, and quantitative approach to characterize the morphology of capillary silica-based monolithic columns by reconstruction from confocal laser scanning microscopy images. The method comprises column pretreatment, image acquisition, image processing, and statistical analysis of the image data. The received morphological data are chord length distributions for the bulk macropore space and skeleton of the silica monolith. The morphological information is shown to be comparable to that derived from transmission electron microscopy, but far easier to access. The approach is generally applicable to silica-based capillary columns, monolithic or particulate. It allows the rapid acquisition of hundreds of longitudinal and cross-sectional images in a single session, resolving a multitude of morphological details in the column.

Porous, polymer-based materials are increasingly used as stationary phases in separation science and catalysis, yet their morphology remains largely unknown. The main difficulty lies in reconciling their soft matter nature with the demands of microscopic imaging techniques. We analyze the morphology of a hyper-cross-linked poly(styrene-divinylbenzene) monolith in capillary column format from a sample volume of 60.5 × 60.5 × 19.9 μm(3) reconstructed by serial block-face scanning electron microscopy. To obtain a suitable specimen, the polymer skeleton was stained with tetraphenyllead and the void space filled with resin before the whole monolith was resin-embedded after removing the fused-silica capillary. Chord length distribution analysis revealed characteristic lengths of 7.32 and 0.73 μm, corresponding to two distinct macropore types. The macroporosity (77% on average) was found to increase systematically from the wall to the center. Our results provide valuable insights into the formation process of the monolith and its stationary-phase properties.