Lateral flow assays (LFAs) are widely employed in a diverse range of applications, including clinical diagnostics, pharmaceutical research, forensics, biotechnology, agriculture, food safety, and environmental analysis. A pivotal component of LFAs is the porous polymeric membrane, which facilitates the capillary-driven movement of fluids, known as “imbibition,” in which a wetting fluid displaces a non-wetting fluid within the pore space of the membrane. This study presents a multi-scale modeling framework designed to investigate the imbibition process within LFAs. The framework integrates microscopic membrane characteristics into a macroscopic two-phase flow model, allowing the simulation of imbibition in membranes with different micro-scale properties and macro-scale profiles. The validity of the model was established through comparative analysis with documented case studies, a macro-scale single-phase flow model, and experimental observations, demonstrating its accuracy in simulating the imbibition process. The study also examines imbibition in various geometric configurations, including bifurcated (Y-shaped) and multi-branch geometries commonly found in multiplexed LFAs. The influence of geometric features such as length ratio, width ratio, branching angle, bifurcation point location, and asymmetry on fluid transport is investigated. Results indicate that membranes with larger branching angles exhibit slower imbibition. In addition, the influence of membrane type on macroscopic flow patterns is evaluated, showing that membranes with lower permeability require longer imbibition times. The insights gained from this research support a data-driven strategy for manipulating wetting behavior within LFAs. This approach can be leveraged to optimize the performance of LFAs and increase their effectiveness in various applications.

Due to their special and unique morphology, porous materials have distinctive properties that make them interesting in several sciences and industries. In industrial applications, a popular parameter to characterize the structure of porous materials is the number of pores per inch (PPI). In this work, we implement a computational algorithm in three-dimensional space to determine the PPI number of a porous structure. The algorithm is composed of different steps: segmentation of pore space using a marker-based watershed algorithm, counting the number of pores and eventually calculating the PPI number. To characterize open-cell porous structures according to their PPI values, we generate three types of them. Firstly, an aligned porous structure with a known number of pores is synthetically generated. Excellent agreement between computational results and known values validates our PPI determination algorithm. Secondly, synthetic isotropic/anisotropic porous structures based on Voronoi tessellation (VT) are studied. Finally, we apply the algorithm to the digital twins of real metal foams. The validated proposed approach with reproducible results serves as a unique standard tool to determine the PPI value, and we discuss that it is more precise than conventional two-dimensional methods that are widely used in industry.

To describe the dynamics of fluid flow in Lateral Flow Assays (LFAs) and to understand the effect of geometry on the propagation speed of the fluid front, a single-phase model is developed. The model can predict wicking time for different geometries. Axisymmetric geometries with changes in their cross sections are studied to understand the wicking behavior. To validate the modeling results, imaging experiments that capture the fluid front are conducted on all geometries. In all cases, convincing agreement between modeling results and experimental data has been observed. Using data-driven information and knowledge about structure–property correlations, it is possible to control wicking processes to establish a desired velocity at a specific position in LFAs. The proposed approach serves as a basis for the creation of a design tool for application-oriented membranes.

This record contains all the necessary data to obtain the results of the study "Geometric flow control in lateral flow assays: Macroscopic single-phase modeling" (https://doi.org/10.1063/5.0093316).

This study presents numerical simulations of rotary kiln reactors for wet biomass carbonization. For this, a numerical tool has been developed resolving the carbonization process in time and space. Biomass particles are represented by Lagrangian particles that collide and form a moving bed. The gas phase is treated as an Eulerian phase. Both phases are fully coupled with the exchange of momentum, energy, and mass of chemical species. The tool is implemented in the open-source OpenFOAM (R) framework and additional submodels for devolatilization, drying and radiation have been developed for the conditions relevant during the carbonization process. In this way, models for the complex physical processes are combined in a single simulation tool. A rotary kiln reactor of laboratory-scale is used to validate the numerical tool and to perform parameter studies to determine biomass conversion in dependence on the wall temperatures. The results also give insight into the sensitivity of biomass to carbon conversion with respect to the biomass moisture content and mass flow rate. The validated tool is used to perform simulations of an industrial-scale rotary kiln reactor, which are carried out on a supercomputer on up to 1120 CPU cores. The simulations demonstrate the effect of different wall temperatures on the optimal conversion of biomass to char and help to choose the optimal wall temperatures depending on the biomass properties.

If water pipes, which are heated from the outside, are lined with an open porous inner structure, the heat can quickly reach the water via the large contact surface. At the same time, the flow resistance increases due to the presence of the interior. We aim for computationally designing an internal structure that is advantageous for both heat transfer and flow. In this paper we present our path from digital models to metallic pipe components with specifically adjusted properties: First, we design digital models for line pipe elements and qualify them with the help of computer simulations. As a next step, the algorithmically generated samples are printed in 3D. The 3D-printed polylactide models serve as prototypes for the production of metallic pipes, which are then tested in experiments. In this work, three types of inner structures are evaluated: Metal foam, cuboid fins and curved fins. For better comparability, we provide them with almost the same specific surface area and porosity. The use of open-pore metal foams is advantageous for greater heat transfer and fins enable smaller pressure drop. (C) 2020 Elsevier Ltd. All rights reserved.

Carbonization is a key process to increase the energy density of high moisture containing biomasses and biogenic wastes and to provide multi-purpose raw chemicals for further applications. Steam assisted carbonization is a kind of slow pyrolysis, in which wet biomass is treated continuously in superheated steam at elevated temperature and atmospheric pressure. Rotary kiln reactors due to their flexibility and easy control of operating conditions are well suited for this process. In this work a numerical simulation tool based on an Eulerian-Langrangian approach has been developed to simulate the carbonization of biomasses in rotary kiln reactors resolved in time and space by combining existing OpenFOAM features and developing new physical models. This study demonstrates the features of this extended and validated Eulerian-Lagrangian approach for simulating dense particulate multiphase flows in large-scale rotary kiln reactors. The focus is to using the new tool to aid the design of large scale rotary kiln reactors by performing parameter studies. The simulations of this kind of large scale reactors require large computational resources on supercomputers. Therefore, a further focus lies in different approaches to reduce the computational effort while keeping the accuracy at an acceptable level. By using the MP-PIC model, computing time increases linearly with the number of biomass particles instead of exponentially with the DPM model. The optimal cell size has been found to be about twice the largest particle diameter. By choosing the optimal domain decomposition method, simulation time can be reduced by a factor of 1/10. Introducing a solver frequency parameter to the DOM radiation model can help to reduce simulation times further by a factor of 1/8 while decreasing the accuracy by only 2%. Parallel scaling tests show good performance with over 1000 CPU cores. These results show that simulations with a total of 40,000 CPU-hours per studied case become feasible proving the developed solver to be an efficient tool for the design of rotary kiln reactors. at every time step, every 10 th and every 20 th time step are compared (solver frequency of 10 and 20). The results are compared with the refined case with 128 directions and the solver frequency of one in Table . By introducing the solver frequency of 20 and reducing the number of discrete directions to 72, the computation time can be reduced by a factor of 1/7 while decreassing the average particle temperatures by only 2.7% . Results are obtained from runs with 16 parallel CPU cores.

Microfluidic devices often contain several phases. Their design can be supported by interface-resolving numerical simulations, requiring accurate methods and validated computer codes. Especially challenging are submillimetre air bubbles in water due to their large density contrast and dominance of surface tension. Here, we evaluate two numerical methods implemented in OpenFOAM®, namely the standard solver interFoam with an algebraic volume-of-fluid method relying on a sharp interface representation and phaseFieldFoam relying on the phase-field method with diffuse interface representation. For a circular bubble in static equilibrium, we explore the impacts of uniform grid resolution and bubble size on bubble shape, mass conservation, pressure jump and spurious currents. While the standard interFoam solver exhibits excellent mass conservation with errors below 0.1% on fine grids, it lacks the accuracy to predict reasonable physics for a bubble in microfluidic systems. At higher resolution, large spurious currents significantly displace and deform the bubble, which is oscillating with resolution dependent mode and frequency. Furthermore, the pressure jump is consistently underestimated by more than 10%. The solver phaseFieldFoam suffers from much larger mass losses of up to 2%, which decrease as the ratio between interface thickness and bubble diameter decreases provided the diffuse interface region is adequately resolved. Spurious currents are very low and the bubble remains circular preserving its initial position with an error in pressure jump below 1%.