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Estimation of characteristic coagulation time based on Brownian coagulation theory and stability ratio modeling using electrokinetic measurements

Abstract : Coagulation is a key process particularly in the field of polymer production. Controlling this phenomenon at industrial scale is a significant challenge because it is highly dependent on the operating conditions and the equipment used for the coagulation process. Poor control of coagulation may strongly affect the quality and the reproducibility of the final aggregates. In the objective of facilitating the choice of both adequate operating conditions and suitable devices for coagulation processes, this paper presents a method to estimate characteristic coagulation time of colloidal suspensions as a function of pH, ionic strength and volume fraction of particles. This method is based on Brownian coagulation theory, assuming very small initial particles. The collision efficiency is taken into account by the introduction of a stability ratio. This ratio is calculated using models that have been adjusted using electrokinetic measurements. The developed methodology is then applied to an industrial latex in order to estimate the operating conditions to fully destabilized the latex. Orders of magnitude of characteristic coagulation time are also obtained. Since perfect mixing of the colloidal suspension and the coagulant is necessary to obtain satisfactory aggregate properties, the characteristic coagulation time is compared with the mixing time for different mixing technologies, providing useful information for process design.
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Submitted on : Friday, September 20, 2019 - 9:09:47 AM
Last modification on : Thursday, June 2, 2022 - 4:12:05 PM
Long-term archiving on: : Sunday, February 9, 2020 - 1:20:52 AM

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Kevin Lachin, Nathalie Le Sauze, Nathalie Di Miceli Raimondi, Joelle Aubin, Michel Cabassud, et al.. Estimation of characteristic coagulation time based on Brownian coagulation theory and stability ratio modeling using electrokinetic measurements. Chemical Engineering Journal, Elsevier, 2019, 369, pp.818-827. ⟨10.1016/j.cej.2019.03.130⟩. ⟨hal-02292121⟩

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