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Computer design of microfluidic mixers for protein/RNA folding studies

Kinetic studies of biological macromolecules increasingly use microfluidic mixers to initiate and monitor reaction progress. A motivation for using microfluidic mixers is to reduce sample consumption and decrease mixing time to microseconds. Some applications, such as small-angle x-ray scattering, a...

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Detalles Bibliográficos
Autores principales: Inguva, Venkatesh, Kathuria, Sagar V., Bilsel, Osman, Perot, Blair James
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6010218/
https://www.ncbi.nlm.nih.gov/pubmed/29924842
http://dx.doi.org/10.1371/journal.pone.0198534
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author Inguva, Venkatesh
Kathuria, Sagar V.
Bilsel, Osman
Perot, Blair James
author_facet Inguva, Venkatesh
Kathuria, Sagar V.
Bilsel, Osman
Perot, Blair James
author_sort Inguva, Venkatesh
collection PubMed
description Kinetic studies of biological macromolecules increasingly use microfluidic mixers to initiate and monitor reaction progress. A motivation for using microfluidic mixers is to reduce sample consumption and decrease mixing time to microseconds. Some applications, such as small-angle x-ray scattering, also require large (>10 micron) sampling areas to ensure high signal-to-noise ratios and to minimize parasitic scattering. Chaotic to marginally turbulent mixers are well suited for these applications because this class of mixers provides a good middle ground between existing laminar and turbulent mixers. In this study, we model various chaotic to marginally turbulent mixing concepts such as flow turning, flow splitting, and vortex generation using computational fluid dynamics for optimization of mixing efficiency and observation volume. Design iterations show flow turning to be the best candidate for chaotic/marginally turbulent mixing. A qualitative experimental test is performed on the finalized design with mixing of 10 M urea and water to validate the flow turning unsteady mixing concept as a viable option for RNA and protein folding studies. A comparison of direct numerical simulations (DNS) and turbulence models suggests that the applicability of turbulence models to these flow regimes may be limited.
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spelling pubmed-60102182018-07-06 Computer design of microfluidic mixers for protein/RNA folding studies Inguva, Venkatesh Kathuria, Sagar V. Bilsel, Osman Perot, Blair James PLoS One Research Article Kinetic studies of biological macromolecules increasingly use microfluidic mixers to initiate and monitor reaction progress. A motivation for using microfluidic mixers is to reduce sample consumption and decrease mixing time to microseconds. Some applications, such as small-angle x-ray scattering, also require large (>10 micron) sampling areas to ensure high signal-to-noise ratios and to minimize parasitic scattering. Chaotic to marginally turbulent mixers are well suited for these applications because this class of mixers provides a good middle ground between existing laminar and turbulent mixers. In this study, we model various chaotic to marginally turbulent mixing concepts such as flow turning, flow splitting, and vortex generation using computational fluid dynamics for optimization of mixing efficiency and observation volume. Design iterations show flow turning to be the best candidate for chaotic/marginally turbulent mixing. A qualitative experimental test is performed on the finalized design with mixing of 10 M urea and water to validate the flow turning unsteady mixing concept as a viable option for RNA and protein folding studies. A comparison of direct numerical simulations (DNS) and turbulence models suggests that the applicability of turbulence models to these flow regimes may be limited. Public Library of Science 2018-06-20 /pmc/articles/PMC6010218/ /pubmed/29924842 http://dx.doi.org/10.1371/journal.pone.0198534 Text en © 2018 Inguva et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Inguva, Venkatesh
Kathuria, Sagar V.
Bilsel, Osman
Perot, Blair James
Computer design of microfluidic mixers for protein/RNA folding studies
title Computer design of microfluidic mixers for protein/RNA folding studies
title_full Computer design of microfluidic mixers for protein/RNA folding studies
title_fullStr Computer design of microfluidic mixers for protein/RNA folding studies
title_full_unstemmed Computer design of microfluidic mixers for protein/RNA folding studies
title_short Computer design of microfluidic mixers for protein/RNA folding studies
title_sort computer design of microfluidic mixers for protein/rna folding studies
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6010218/
https://www.ncbi.nlm.nih.gov/pubmed/29924842
http://dx.doi.org/10.1371/journal.pone.0198534
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