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Understanding the Residence Time Distribution in a Transient Inline Spiking System: Modeling, Experiments, and Simulations

A transient inline spiking system is a promising tool for evaluating the performance of a virus filter in continuous operation. For better implementation of the system, we performed a systematic analysis to understand the residence time distribution (RTD) of inert tracers in the system. We aimed to...

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Autores principales: Hwang, Minsun, Wang, Junsuk, Jung, Seon Yeop
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10143522/
https://www.ncbi.nlm.nih.gov/pubmed/37103802
http://dx.doi.org/10.3390/membranes13040375
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author Hwang, Minsun
Wang, Junsuk
Jung, Seon Yeop
author_facet Hwang, Minsun
Wang, Junsuk
Jung, Seon Yeop
author_sort Hwang, Minsun
collection PubMed
description A transient inline spiking system is a promising tool for evaluating the performance of a virus filter in continuous operation. For better implementation of the system, we performed a systematic analysis to understand the residence time distribution (RTD) of inert tracers in the system. We aimed to understand the RTD of a salt spike, not retained onto or within the membrane pore, to focus on its mixing and spreading within the processing units. A concentrated NaCl solution was spiked into a feed stream as the spiking duration ([Formula: see text]) was varied from 1 to 40 min. A static mixer was employed to mix the salt spike with the feed stream, which then passed through a single-layered nylon membrane inserted in a filter holder. The RTD curve was obtained by measuring the conductivity of the collected samples. An analytical model, the PFR-2CSTR model, was employed to predict the outlet concentration from the system. The slope and peak of the RTD curves were well-aligned with the experimental findings when  [Formula: see text] = 4.3 min,  [Formula: see text] = 4.1 min, and  [Formula: see text] = 1.0 min. CFD simulations were performed to describe the flow and transport of the inert tracers through the static mixer and the membrane filter. The RTD curve spanned more than 30 min, much longer than  [Formula: see text] , since solutes were dispersed within processing units. The flow characteristics in each processing unit correlated with the RTD curves. Our detailed analysis of the transient inline spiking system would be helpful for implementing this protocol in continuous bioprocessing.
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spelling pubmed-101435222023-04-29 Understanding the Residence Time Distribution in a Transient Inline Spiking System: Modeling, Experiments, and Simulations Hwang, Minsun Wang, Junsuk Jung, Seon Yeop Membranes (Basel) Article A transient inline spiking system is a promising tool for evaluating the performance of a virus filter in continuous operation. For better implementation of the system, we performed a systematic analysis to understand the residence time distribution (RTD) of inert tracers in the system. We aimed to understand the RTD of a salt spike, not retained onto or within the membrane pore, to focus on its mixing and spreading within the processing units. A concentrated NaCl solution was spiked into a feed stream as the spiking duration ([Formula: see text]) was varied from 1 to 40 min. A static mixer was employed to mix the salt spike with the feed stream, which then passed through a single-layered nylon membrane inserted in a filter holder. The RTD curve was obtained by measuring the conductivity of the collected samples. An analytical model, the PFR-2CSTR model, was employed to predict the outlet concentration from the system. The slope and peak of the RTD curves were well-aligned with the experimental findings when  [Formula: see text] = 4.3 min,  [Formula: see text] = 4.1 min, and  [Formula: see text] = 1.0 min. CFD simulations were performed to describe the flow and transport of the inert tracers through the static mixer and the membrane filter. The RTD curve spanned more than 30 min, much longer than  [Formula: see text] , since solutes were dispersed within processing units. The flow characteristics in each processing unit correlated with the RTD curves. Our detailed analysis of the transient inline spiking system would be helpful for implementing this protocol in continuous bioprocessing. MDPI 2023-03-25 /pmc/articles/PMC10143522/ /pubmed/37103802 http://dx.doi.org/10.3390/membranes13040375 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Hwang, Minsun
Wang, Junsuk
Jung, Seon Yeop
Understanding the Residence Time Distribution in a Transient Inline Spiking System: Modeling, Experiments, and Simulations
title Understanding the Residence Time Distribution in a Transient Inline Spiking System: Modeling, Experiments, and Simulations
title_full Understanding the Residence Time Distribution in a Transient Inline Spiking System: Modeling, Experiments, and Simulations
title_fullStr Understanding the Residence Time Distribution in a Transient Inline Spiking System: Modeling, Experiments, and Simulations
title_full_unstemmed Understanding the Residence Time Distribution in a Transient Inline Spiking System: Modeling, Experiments, and Simulations
title_short Understanding the Residence Time Distribution in a Transient Inline Spiking System: Modeling, Experiments, and Simulations
title_sort understanding the residence time distribution in a transient inline spiking system: modeling, experiments, and simulations
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10143522/
https://www.ncbi.nlm.nih.gov/pubmed/37103802
http://dx.doi.org/10.3390/membranes13040375
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