Filter cake formation is the predominant phenomenon limiting the filtration performance of membrane separation processes. However, the filter cake’s behavior at the particle scale, which determines its overall cake behavior, has only recently come into the focus of scientists, leaving open questions about its formation and filtration behavior. The present study contributes to the fundamental understanding of soft filter cakes by analyzing the influence of the porous membrane’s morphology on crystal formation and the compaction behavior of soft filter cakes under filtration conditions. Microfluidic chips with nanolithographic imprinted filter templates were used to trigger the formation of crystalline colloidal filter cakes formed by soft microgels. The soft filter cakes were observed via confocal laser scanning microscopy (CLSM) under dead-end filtration conditions. Colloidal crystal formation in the cake, as well as their compaction behavior, were analyzed by optical visualization and pressure data. For the first time, we show that exposing the soft cake to a crystalline filter template promotes the formation of colloidal crystallites and that soft cakes experience gradient compression during filtration.

/pdf/templating-the-morphology-of-soft-microgel-assemblies-using-4wcfvit47m.pdf

Templating the morphology of soft microgel assemblies using a nanolithographic 3D-printed membrane

Over the past two decades, microfluidics has made significant contributions to material and life sciences, particularly via the design of nano-, micro- and mesoscale materials such as nanoparticles, micelles, vesicles, emulsion droplets, and microgels. Unmatched in control over a multitude of material parameters, microfluidics has also shed light on fundamental aspects of material design such as the early stages of nucleation and growth processes as well as structure evolution. Exemplarily, polymer hydrogel particles can be formed via microfluidics with exact control over size, shape, functionalization, compartmentalization, and mechanics that is hardly found in any other processing method. Interestingly, the utilization of microfluidics for material design largely focuses on the fabrication of single entities that act as reaction volume for organic and cell-free biosynthesis, cell mimics, or local environment for cell culturing. In recent years, however, hydrogel design has shifted towards structures that integrate a large variety of functions, e.g., to address the demands for sensing tasks in a complex environment or more closely mimicking architecture and organization of tissue by multiparametric cultures. Hence, this review provides an overview of recent literature that explores microfluidics for fabricating hydrogel materials that go well beyond common length scales as well as the structural and functional complexity of microgels necessary to produce hierarchical hydrogel structures. We focus on examples that utilize microfluidics to design microgel-based assemblies, on microfluidically made polymer microgels for 3D bioprinting, on hydrogels fabricated by microfluidics in a continuous fashion, like fibers, and on hydrogel structures that are shaped by microchannels. 

From microfluidics to hierarchical hydrogel materials

During soft matter filtration, colloids accumulate in a compressible porous cake layer on top of the membrane surface. The void size between the colloids predominantly defines the cake-specific permeation resistance and the corresponding filtration efficiency. While higher fluxes are beneficial for the process efficiency, they compress the cake and increase permeation resistance. However, it is not fully understood how soft particles behave during cake formation and how their compression influences the overall cake properties. This study visualizes the formation and compression process of soft filter cakes in microfluidic model systems. During cake formation, we analyze single-particle movements inside the filter cake voids and how they interact with the whole filter cake morphology. During cake compression, we visualize reversible and irreversible compression and distinguish the two phenomena. Finally, we confirm the compression phenomena by modeling the soft particle filter cake using a CFD-DEM approach. The results underline the importance of considering the compression history when describing the filter cake morphology and its related properties. Thus, this study links single colloid movements and filter cake compression to the overall cake behavior and narrows the gap between single colloid events and the filtration process.

/pdf/particle-movements-provoke-avalanche-like-compaction-in-soft-iruyhsok7o.pdf

Particle movements provoke avalanche-like compaction in soft colloid filter cakes

Automated tangential-flow diafiltration device

Plugging of hollow fiber lumen by a gel: Threshold operating conditions unraveled by simulations

The filtration performance of soft colloid suspensions suffers from the agglomeration of the colloids on the membrane surface as filter cakes. Backflushing of fluid through the membrane and cross-flow flushing across the membrane are widely used methods to temporally remove the filter cake and restore the flux through the membrane. However, the phenomena occurring during the recovery of the filtration performance are not yet fully described. In this study, we filtrate poly(N-isopropylacrylamide) microgels and analyze the filter cake in terms of its composition and its dynamic mobility during removal using on-line laser scanning confocal microscopy. First, we observe uniform cake build-up that displays highly ordered and amorphous regions in the cake layer. Second, backflushing removes the cake in coherent pieces and their sizes depend on the previous cake build-up. And third, cross-flow flushing along the cake induces a pattern of longitudinal ridges on the cake surface, which depends on the cross-flow velocity and accelerates cake removal. These observations give insight into soft colloid filter cake arrangement and reveal the cake's unique behaviour exposed to shear-stress.

/pdf/unravelling-colloid-filter-cake-motions-in-membrane-cleaning-3clmkrvetx.pdf

Unravelling colloid filter cake motions in membrane cleaning procedures.

Mechanical power output can be used to quantify performance in order to plan and execute appropriate training programs. To measure mechanical power output during running, the dependent ground reaction forces, among others, should be recorded. Existing wearable devices for determining mechanical power during running do not measure these forces. Instead, they estimate them, for example, based on information from the GPS, inertial sensors, or other kinematic data (Cerezuela-Espejo et al., 2020). With the overall goal of determining mechanical power during running based on kinetic data, we performed long-duration measurements as a first step (Krumm, Koska, Wakode, Odenwald, & Maiwald, 2022). These measurements allow us to estimate vertical ground reaction forces based on plantar pressure. In this paper, we present the regression model developed for this purpose.

Preliminary work on the determination of mechanical power during running based on kinetic data

We use hyperbolic wavelet regression for the fast reconstruction of high-dimensional functions having only low dimensional variable interactions. Compactly supported periodic Chui-Wang wavelets are used for the tensorized hyperbolic wavelet basis on the torus. With a variable transformation we are able to transform the approximation rates and fast algorithms from the torus to other domains. We perform and analyze scattered-data approximation for smooth but arbitrary density functions by using a least squares method. The corresponding system matrix is sparse due to the compact support of the wavelets, which leads to a significant acceleration of the matrix vector multiplication. For non-periodic functions we propose a new extension method. A proper choice of the extension parameter together with the piece-wise polynomial Chui-Wang wavelets extends the functions appropriately. In every case we are able to bound the approximation error with high probability. Additionally, if the function has low effective dimension (i.e. only interactions of few variables), we qualitatively determine the variable interactions and omit ANOVA terms with low variance in a second step in order to decrease the approximation error. This allows us to suggest an adapted model for the approximation. Numerical results show the efficiency of the proposed method.

Laura Lippert

Papers

Unravelling colloid filter cake motions in membrane cleaning procedures.

Preliminary work on the determination of mechanical power during running based on kinetic data

Variable Transformations in combination with Wavelets and ANOVA for high-dimensional approximation