Simultaneous control of copolymer composition and MWD in emulsion copolymerization

Vicente, M.; Rekondo, Jose Ramon Leiza; Asúa, José M.

doi:10.1002/aic.690470712

Cited by 53 publications

(49 citation statements)

References 50 publications

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“…Figure 3 shows the parametric space of q 1 and q 2 (propagation probability of site 1 and 2, respectively) where bimodal mass distributions (M i in Equation (12)) can be found. The lines indicate solutions for Equation (14) and (15). The region where bimodal behavior can be found is larger for FlorySchulz distributions than for dynamic distributions.…”

Section: Model Development and Theoretical Resultsmentioning

confidence: 95%

“…(Contrarily, in semi-batch polymerizations, where the monomer and/or chain transfer concentrations can be abruptly changed through step perturbations, multimodal distributions can be obtained. [15][16][17] However, the introduction of a step perturbation in the concentration trajectory can also be interpreted in terms of the introduction of a new catalytic site with different kinetic properties (q). )…”

Section: Model Development and Theoretical Resultsmentioning

confidence: 99%

“…[11,12] In order to control the MWD of these special polymers (or to obtain the desired MWD) different operation procedures have been applied, such as the use of distinct operation conditions in each reactor of a reactor cascade, [13,14] the variation of chain transfer agent concentrations during semi-batch reactions, [15][16][17] the mixing of different catalysts during olefin polymerizations [18][19][20][21][22] and the mixing of mini-emulsions with different chain transfer agent concentrations during emulsion polymerizations. [23] Despite the useful amount of information that can be obtained from deconvolution techniques, the use of these techniques for kinetic interpretation of polymerization reactions has only been carried out for certain olefin polymerizations.…”

Section: Introductionmentioning

confidence: 99%

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Deconvolution of Molecular Weight Distributions Using Dynamic Flory‐Schulz Distributions

Fortuny

Nele

Melo

et al. 2004

Macro Theory & Simulations

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Summary: The deconvolution of molecular weight distributions (MWDs) may be useful for obtaining information about the polymerization kinetics and properties of catalytic systems. However, deconvolution techniques are normally based on steady‐state assumptions and very little has been reported about the use of non‐stationary approaches for the deconvolution of MWDs. In spite of this, polymerization reactions are often performed in batch or semi‐batch modes. For this reason, dynamic solutions are proposed here for simple kinetic models and are then used for deconvolution of actual MWD data. Deconvolution results obtained with dynamic models are compared to deconvolution results obtained with the standard stationary Flory‐Schulz distributions. For coordination polymerizations, results show that dynamic MWD models are able to describe experimental data with fewer catalytic sites, which indicates that the proper interpretation of the reaction dynamics may be of fundamental importance for kinetic characterization. On the other hand, reaction dynamics induced by modification of chain transfer agent concentration seem to play a minor role in the shape of the MWD in free‐radical polymerizations.This Figure illustrates that MWDs obtained at unsteady conditions should not be deconvoluted with standard steady‐state Flory‐Schulz distributions.imageThis Figure illustrates that MWDs obtained at unsteady conditions should not be deconvoluted with standard steady‐state Flory‐Schulz distributions.

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Section: Model Development and Theoretical Resultsmentioning

confidence: 95%

Section: Model Development and Theoretical Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Deconvolution of Molecular Weight Distributions Using Dynamic Flory‐Schulz Distributions

Fortuny

Nele

Melo

et al. 2004

Macro Theory & Simulations

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“…Note that heat effects of initiation, bimolecular termination and transfer are negligible since the number of propagation steps is orders of magnitude larger than the number of all other reactions. Successful use of a reaction calorimeter has been reported for monitoring emulsion polymerization kinetics, [5][6][7][8][9][10][11][12][13][14][15][16] nucleation effects, [17][18][19] control of molecular weight [20] and other processes. [21][22][23] Emulsion polymerization processes demand for relatively large amounts of surfactant.…”

Section: Introductionmentioning

confidence: 99%

Particle Formation in RAFT‐Mediated Emulsion Polymerization: A Calorimetric Study

Leswin

Meuldijk

Gilbert

et al. 2009

Macromolecular Symposia

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Summary: Ab initio RAFT-mediated semi-continuous emulsion polymerizations with controlled monomer feed have been studied by reaction calorimetry. This online monitoring technique provided detailed information about the onset of the nucleation period in semi-batch processes for emulsion polymerization of styrene and nbutyl acrylate. The reactions were carried out under controlled radical polymerization conditions by employing amphipathic macro-RAFT agents of various degrees of surface activity. For n-butyl acrylate as well as for styrene the more surface active polymeric macro-RAFT agents led to higher initial polymerization rates. Polymerizations with hydrophobic macro-RAFT agents also adapted more quickly to an increased monomer feed than polymerizations with hydrophilic macro-RAFT agents.This points to the presence of more particles when a hydrophobic macro-RAFT agent is used. Hydrophobic macro-RAFT agents demonstrated to be promising for producing latex products with a proper control of particle number and particle size distribution.

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“…A closed-loop control strategy was applied for tracking monomers and CTA trajectories that would lead to desired M w , M n , and MWD through flow rates calculated based on estimations of the amount of monomers and CTA inside the reactor using calorimetry. [30] Control was achieved by feeding the reactor with three streams (one for each comonomer and one for the CTA) following an optimal semistarved strategy. [31] Another approach has used iterative dynamic programing (IDP) to compute the optimal feed rates for monomers and CTA dividing the reaction in discrete intervals and feeding the reactor with three streams, one for the least reactive monomer, one for pre-emulsified monomers and CTA and another preemulsified with the other monomer.…”

Section: Introductionmentioning

confidence: 99%

Automatic Synthesis of Multimodal Polymers

Leonardi¹,

Montgomery²,

Siqueira

et al. 2017

Macro Reaction Engineering

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An automatic molecular weight controller is used in semi‐batch reactions to produce final polymers that contain distinct subpopulations with different molecular weight distributions (MWD). While blending polymers with different MWD is frequently used to make multimodal polymer products, a method is introduced here allowing the multimodal product to be made in successive, automatically controlled stages in the same reactor. The method is demonstrated using free radical polymerization of acrylamide to produce widely separated multimodal MWD. Automatic Continuous Online Monitoring of Polymerization reactions with a Control Interface (ACOMP/CI) was used. Weight average molecular weight (Mw) in the ACOMP/CI was continuously measured with multi‐angle light scattering and ultra‐violet absorption. The controller used two principles: both polymerization rate and instantaneous molecular weight are proportional to monomer concentration. By controlling monomer flow rate into the reactor, the controller produced a targeted amount of polymer with a desired first Mw and then automatically introduced chain transfer agent (CTA) into the reactor to produce a second population of polymers with much lower Mw. Subsequently, reactions were performed to produce trimodal populations. This approach is kindred to multi‐stage synthesis of polymers where distinctly different processes are carried out in succeeding stages to produce polymers with highly specific properties.

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Simultaneous control of copolymer composition and MWD in emulsion copolymerization

Cited by 53 publications

References 50 publications

Deconvolution of Molecular Weight Distributions Using Dynamic Flory‐Schulz Distributions

Deconvolution of Molecular Weight Distributions Using Dynamic Flory‐Schulz Distributions

Particle Formation in RAFT‐Mediated Emulsion Polymerization: A Calorimetric Study

Automatic Synthesis of Multimodal Polymers

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