Flow physics and mixing quality in a confined impinging jet mixer
Source abstract
Abstract
Due to their ability to provide efficient mixing at small scales, confined impinging jet mixers (CIJMs) are employed widely in nanoparticle assembly processes such as flash nanoprecipitation and flash nanocomplexation, which require rapid mixing. In this mixing device, two jets from opposite directions impinge directly on each other forming a thin shear layer that breaks down rapidly into small flow structures. This enables effective mixing of the species transported by each jet by drastically reducing the diffusion distance. In the present study, the mixing performance of a commonly used cylindrical CIJM is examined by direct numerical simulations. Analysis of the simulation results indicates that the interaction of the shear layer with the inner walls of the CIJM is critical in inducing a range of instabilities in the impinging jet flow. By examining flow structures, statistical quantities, and metrics, we have characterized and quantified the mixing quality of a binary mixture in the CIJM. Product uniformity in processes such as precipitation and complexation is expected to depend on the residence time of the constituents, and this quantity is also calculated and compared for the cases with different jet Reynolds numbers. The jet Reynolds numbers of Re = 200, 600, and 1000 are considered, and the simulation results show that the CIJM achieves very good mixing for the Re = 600 and Re = 1000 cases. It is also found that the Re = 600 case performs slightly better than the other cases in terms of uniformity of the residence time. These quantitative analyses offer useful insights into the mechanism of nanoparticle size control and uniformity afforded by the unique flow physics and mixing characteristics in the CIJMs.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Lattice Boltzmann Simulation Studies · Fluid Dynamics and Turbulent Flows · Particle Dynamics in Fluid Flows
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Mechanical Engineering, Johns Hopkins University 1 , Baltimore, Maryland 21218, USA
Biomedical Engineering, Johns Hopkins University 2 , Baltimore, Maryland 21287, USA
Institute for NanoBioTechnology, Johns Hopkins University 3 , Baltimore,Maryland 21218, USA
Materials Science and Engineering, Johns Hopkins University 4 , Baltimore,Maryland 21218, USA
Funding
National Institutes of Health
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