Filtration of aqueous colloidal ceria slurries using fibrous filters – An experimental and simulation study

Nanoparticle Diffusion in Respiratory Mucus Influenced by Mucociliary Clearance: A Review of Mathematical Modeling

Background: Inhalation and deposition of particles in human airways have attracted considerable attention due to importance of particulate pollutants, transmission of infectious diseases, and therapeutic delivery of drugs at targeted areas. We summarize current state-of-the art research in particle deposition on airway surface liquid (ASL) influenced by mucociliary clearance (MCC) by identifying areas that need further investigation. Methodology: We aim to review focus on governing and constitutive equations describing MCC geometry followed by description of mathematical modeling of ciliary forces, mucus rheology properties, and numerical approaches to solve modified time-dependent Navier-Stokes equations. We also review mathematical modeling of particle deposition in ASL influenced by MCC, particle transport in ASL in terms of Eulerian and Lagrangian approaches, and discuss the corresponding mass transport issues in this layer. Whenever required, numerical predictions are contrasted with the pertinent experimental data. Results: Results indicate that mean mucus and periciliary liquid velocities are strongly influenced by mucus rheological characteristics as well as ciliary abnormalities. However, most of the currently available literature on mucus fiber spacing, ciliary beat frequency, and particle surface chemistry is based on particle deposition on ASL by considering a fixed value of ASL velocity. The effects of real ASL flow regimes on particle deposition in this layer are limited. In addition, no other study is available on modeling nonhomogeneous and viscoelastic characteristics of mucus layer on ASL drug delivery. Conclusion: Simplification of assumptions on governing equations of drug delivery in ASL influenced by MCC leads to imposing some limitations on numerical results.

3D Phage-based biomolecular filter for effective high throughput capture of Salmonella Typhimurium in liquid streams

Foodborne illnesses caused by pathogens on fresh produce remain one of the most critical food safety problems the world faces. The recalls of pasta salad in 2018 and pre-cut melons in 2019 imply current methods in identifying the source of pathogens and outbreak prevention are inappropriate and time consuming. In this article, a new technology, called the 3D phage-based biomolecular filter, was developed to simultaneously capture and concentrate foodborne pathogens from large volumes of liquid streams (food liquid or wash water streams). The 3D phage-based filter consisted of phage-immobilized magnetoelastic (ME) filter elements, a filter pipe system, and a uniform magnetic field to fix and align the ME filter elements in the 3D filter column. The closely packed ME filter elements display a 3D layered structure which allows for enhanced surface interaction of the immobilized bacteriophage with specific pathogens in the passing liquid streams. As a result, a pathogen capture rate of more than 90% was achieved at a high flow rate of 3 mm/s with 20,000 ME filter elements. The capability of the 3D phage-based filter to capture pathogens in liquid streams at different filter element packing densities was further validated by experiments, finite element analysis and theoretical calculations. The capture rate increases significantly with larger numbers of ME filter elements placed in the testing pipe, and the turbulence flow induced by the 3D stacking of ME filter elements can further improve the capture efficiency. This technology enables rapid capture and analysis of large volume of water in processing fresh fruit and vegetables for the presence of small quantities of pathogens, which will ultimately benefit producers, the food industry, and society with improved food safety and production efficiency.

Universal inherent fluctuations in statistical counting of large particles in slurry used for semiconductor manufacturing

In the chemical mechanical polishing process of semiconductor manufacturing, the concentration of ‘large’ particles (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\ge $$\end{document}≥0.5 μm) in the slurry, which is considerably larger in size than the main abrasives (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\approx $$\end{document}≈ 0.1 μm), is a critical parameter that strongly influences manufacturing defects, yields, and reliabilities of large-scale-integrated circuits. Various instruments, so-called particle counters, based on light scattering, light extinction, and holography techniques have been developed to measure and monitor the large particle concentration in semiconductor fabs in real time. However, sizeable fluctuation in the measured particle concentration complicates the statistical process control in the fabs worldwide. Here, we show that an inherent fluctuation exists in the counting of large particles, which is universal, independent of instrument type, and quantitatively determined by the instrument’s operation parameters. We analytically derive a statistical theory of the fluctuation based on Poisson statistics and validate the theory through experiments and Monte-Carlo simulation. Furthermore, we provide a strategy to enhance the measurement accuracy by statistically adjusting the instrumental parameters commonly involved in the particle counters. The present results and analyses could be useful for statistical process control in semiconductor fabs to prevent large particle-induced defects such as micro-scratches and pits on wafers.

Study of particle rebound and deposition on fibre surface

Fibrous filters, which are the most commonly used means of particle filtration, are generally characterized by the air pressure drop and filtration efficiency. The nature of particle movement and interaction between the particle and fibre is of great importance for measuring the filtration efficiency of fibrous filters. Majority of previous studies investigated particle trajectory and deposition using the ideal trapping model, which assumed that particles will be trapped once contacted with a solid surface (fibre or deposited particle). This work investigates the dynamic performance of particle rebound and statistically analyses the deposition/accumulation of particles on a fibre surface. We use the computational fluid dynamics (CFD) method to calculate the flow field around a row of fibres. Then, we utilize a particle adherence and rebound criterion and simulate the particle trajectory and deposition using a self-developed solver in Fortran code. Effects of face velocity, particle diameter, and particle rebound characteristics on particle rebound and accumulation around one of the fibres are investigated. Additionally, the trajectories and accumulation of particles on the fibre surface are visually presented. Finally, the filtration efficiency of a single fibre is compared with published results. It is found that effects of particle rebound on the particle trajectory and deposition are significantly related to the face velocity and particle diameter. With considering the particle rebound, the filtration efficiency of a single fibre is obviously different from that of previous studies.