A mathematical modeling study of the influence of small amounts of KCl solution tracers on mixing in water and residence time distribution of tracers in a continuous flow reactor-metallurgical tundish

2015 ◽  
Vol 137 ◽  
pp. 914-937 ◽  
Author(s):  
Chao Chen ◽  
Lage Tord Ingemar Jonsson ◽  
Anders Tilliander ◽  
Guoguang Cheng ◽  
Pär Göran Jönsson
2019 ◽  
Author(s):  
Marcus Reis ◽  
Travis Varner ◽  
Frank Leibfarth

<p>Continuous-flow chemistry is emerging as an enabling technology for the synthesis of precise polymers. Despite recent advances in this rapidly growing field, there remains a need for a fundamental understanding of how fluid dynamics in tubular reactors influence polymerizations. Herein, we report a comprehensive study of how laminar flow influences polymer structure and composition. Tracer experiments coupled with in-line UV-vis spectroscopy demonstrate how viscosity, tubing diameter, and reaction time affect the residence time distribution (RTD) of fluid in reactor geometries relevant for continuous-flow polymerizations. We found that the breadth of the RTD has strong, statistical correlations with reaction conversion, polymer molar mass, and dispersity for polymerizations conducted in continuous flow. These correlations were demonstrated to be general to a variety of different reaction conditions, monomers, and polymerization mechanisms. Additionally, these findings inspired the design of a droplet flow reactor that minimizes the RTD in continuous-flow polymerizations and enables the continuous production of well-defined polymer at a rate of 1.4 kg/day. </p>


2019 ◽  
Author(s):  
Marcus Reis ◽  
Travis Varner ◽  
Frank Leibfarth

<p>Continuous-flow chemistry is emerging as an enabling technology for the synthesis of precise polymers. Despite recent advances in this rapidly growing field, there remains a need for a fundamental understanding of how fluid dynamics in tubular reactors influence polymerizations. Herein, we report a comprehensive study of how laminar flow influences polymer structure and composition. Tracer experiments coupled with in-line UV-vis spectroscopy demonstrate how viscosity, tubing diameter, and reaction time affect the residence time distribution (RTD) of fluid in reactor geometries relevant for continuous-flow polymerizations. We found that the breadth of the RTD has strong, statistical correlations with reaction conversion, polymer molar mass, and dispersity for polymerizations conducted in continuous flow. These correlations were demonstrated to be general to a variety of different reaction conditions, monomers, and polymerization mechanisms. Additionally, these findings inspired the design of a droplet flow reactor that minimizes the RTD in continuous-flow polymerizations and enables the continuous production of well-defined polymer at a rate of 1.4 kg/day. </p>


2019 ◽  
Vol 52 (9) ◽  
pp. 3551-3557 ◽  
Author(s):  
Marcus H. Reis ◽  
Travis P. Varner ◽  
Frank A. Leibfarth

Processes ◽  
2019 ◽  
Vol 7 (9) ◽  
pp. 615 ◽  
Author(s):  
Peter Toson ◽  
Pankaj Doshi ◽  
Dalibor Jajcevic

The tanks-in-series model (TIS) is a popular model to describe the residence time distribution (RTD) of non-ideal continuously stirred tank reactors (CSTRs) with limited back-mixing. In this work, the TIS model was generalised to a cascade of n CSTRs with non-integer non-negative n. The resulting model describes non-ideal back-mixing with n > 1. However, the most interesting feature of the n-CSTR model is the ability to describe short recirculation times (bypassing) with n < 1 without the need of complex reactor networks. The n-CSTR model is the only model that connects the three fundamental RTDs occurring in reactor modelling by variation of a single shape parameter n: The unit impulse at n→0, the exponential RTD of an ideal CSTR at n = 1, and the delayed impulse of an ideal plug flow reactor at n→∞. The n-CSTR model can be used as a stand-alone model or as part of a reactor network. The bypassing material fraction for the regime n < 1 was analysed. Finally, a Fourier analysis of the n-CSTR was performed to predict the ability of a unit operation to filter out upstream fluctuations and to model the response to upstream set point changes.


2015 ◽  
Vol 357 (16-17) ◽  
pp. 3671-3680 ◽  
Author(s):  
Sándor B. Ötvös ◽  
Aliz Szloszár ◽  
István M. Mándity ◽  
Ferenc Fülöp

2009 ◽  
Vol 74 (6) ◽  
pp. E322-E327 ◽  
Author(s):  
Sanjay Sarang ◽  
Brian Heskitt ◽  
Priyank Tulsiyan ◽  
Sudhir K. Sastry

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