Despite their excellent capabilities, wide implementation of membranes for oil/water emulsion separation is limited due to severe fouling. To date, microscale dynamics of the oil-water-membrane system are poorly understood. The present study uses confocal microscopy at unprecedented resolution for direct observation of oil droplet deposition, deformation, and detachment during separation and cleaning, respectively. The 3D shape of the droplets was imaged as a function of the permeation rate, J, droplet radius, R, membrane permeance, k, water viscosity, μ, and the water/oil interfacial tension coefficient, σ. These parameters yield a modified capillary number, [Formula: see text] = μVR/σk, which accounts for the extra viscous "suction" at close proximity to the membrane surface. A clear correlation was observed between the degree of droplet deformation and an increasing [Formula: see text]. Furthermore, the reversibility of droplet deposition and membrane performance were assessed through microscopic surface coverage and flux recovery analysis. In general, operation at a low flux (3.9 μm/s) yields spherical droplets that are easily removed by crossflow cleaning, whereas a high flux (85 μm/s) leads to significant deformation and mostly irreversible deposition. These results shed important new insight on the influence of hydrodynamic conditions on fouling reversibility during emulsion separation, and may guide better design of surface-modified membranes.
<p>Wastewater based epidemiology has been on a fast track of adoption since COVID-19 pandemic. Methodologies for SARS-CoV-2 and other pathogens sewer surveillance evolve around the world, defining best practices for sampling to reach an accurate viral load estimation. These methodologies focused on samples collected from wastewater treatment plants (WWTP). In this session, we present an approach for sewage in-network monitoring that allows a better and targeted understanding of morbidity for SARS-CoV-2 and Influenza viruses. This approach can narrow infected regions and potentially allocate limited resources when needed in a specified community.</p> <p>&#160;</p> <p><strong>Keywords</strong>: Wastewater Based Epidemiology (WBE); Source apportionment; Public health monitoring.</p>
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.