Estimation of the reactivity ratios in the copolymerization of acrylic acid and acrylamide from composition–conversion measurements by an improved nonlinear least-squares method

Shawki, S. M.; Hamielec, A. E.

doi:10.1002/app.1979.070231102

Cited by 40 publications

(36 citation statements)

References 3 publications

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“…A statistical technique, no matter how novel or sophisticated it might be, cannot compensate for low (or complete lack of) information content in the data. The estimation results and analysis are not to be trusted and no valid conclusions can be drawn based on an ill‐conditioned data set (which may arise either from badly designed experiments or from experimental analysis with significant error). The same trends and observations were also confirmed with many other copolymerization systems, including data sets from low, moderate and high conversion levels from acrylamide/acrylic acid (Bourdais,20 Shawki and Hamielec21), styrene/methyl methacrylate (Burke et al,22 O' Driscoll and Huang 23), glycidyl methacrylate/styrene (Wang and Hutchinson24), and several systems from Gao and Penlidis 25. The similar results from these additional systems (not cited here for the sake of brevity) corroborated the validity of the trends described in the four case studies of the current paper.…”

Section: Resultssupporting

confidence: 75%

“…The same trends and observations were also confirmed with many other copolymerization systems, including data sets from low, moderate and high conversion levels from acrylamide/acrylic acid (Bourdais,20 Shawki and Hamielec21), styrene/methyl methacrylate (Burke et al,22 O' Driscoll and Huang 23), glycidyl methacrylate/styrene (Wang and Hutchinson24), and several systems from Gao and Penlidis 25. The similar results from these additional systems (not cited here for the sake of brevity) corroborated the validity of the trends described in the four case studies of the current paper.…”

Section: Resultssupporting

confidence: 75%

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Reactivity Ratio Estimation from Cumulative Copolymer Composition Data

Kazemi

Duever

Penlidis

2011

Macro Reaction Engineering

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The goal is to present an alternative technique for reactivity ratio estimation in copolymerization. Typically, reactivity ratios are estimated using the instantaneous copolymer composition equation, based on low conversion copolymer composition data. However, using experimental data from the full copolymerization trajectory would, in principle, be more advantageous, and shy away from commonly used restrictive assumptions. Estimation using cumulative copolymerization data and models eliminates the difficulties associated with stopping reactions at low conversion, while one gains to study the full polymerization trajectory. The error‐in‐variables‐model (EVM) method is used for parameter estimation. Two cumulative model forms, the analytical integration of the differential composition equation and the one resulting from the direct numerical integration of this equation, are employed. Using these two types of models improves the reactivity ratio estimation and, in particular, the latter model form is a more reliable and direct method of estimating reactivity ratios.

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Section: Resultssupporting

confidence: 75%

Section: Resultssupporting

confidence: 75%

Reactivity Ratio Estimation from Cumulative Copolymer Composition Data

Kazemi

Duever

Penlidis

2011

Macro Reaction Engineering

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“…This complies with previously published k p values of the homopolymerizations of the investigated monomers . To gain an insight into the monomer distribution within the polymer chain, the calculation of the reactivity ratios is indispensable and was performed using eq . The reactivity ratios of EtOx and BocOx were found to be similar ( r BocOx = 1.02 ≈ 1 ≈ r EtOx = 0.98), suggesting the formation of random copolymers .…”

Section: Resultssupporting

confidence: 72%

Comparison of random and gradient amino functionalized poly(2‐oxazoline)s: Can the transfection efficiency be tuned by the macromolecular structure?

Hertz

Leiske

Wloka

et al. 2018

J. Polym. Sci. Part A: Polym. Chem.

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Poly(ethylene imine) can be considered as the gold standard for DNA delivery into cells in vitro, but severe cytotoxic side‐effects and inapplicability for targeted approaches in vivo urgently call for the design of new gene carriers. Since poly(2‐oxazoline)s (P(Ox)s) can be easily synthesized and modified, this polymer class might be ideal for the optimization of polymeric transfection processes. The utilization of 2‐methyl‐2‐oxazoline (MeOx) and 2‐ethyl‐2‐oxazoline (EtOx) is also known to be beneficial because these monomers were suggested to overcome solubility issues, mediate stealth behavior and, consequently, facilitate a reduction of cytotoxicity. A series of amino (AmOx) functionalized P(Ox) copolymers with either MeOx (gradient copolymers) or EtOx (random copolymers) was synthesized, deprotected and biochemically characterized regarding cytotoxicity, polyplex formation ability, cellular uptake, and transfection efficiency. Polymers with percentages of AmOx higher than 35 mol % showed stable polyplex formation and also an increase in cytotoxicity. All elucidated P(Ox)s revealed a poor transfection efficiency in both L929 and Hepa1‐6 cell lines. However, the investigations contribute to the understanding of the influence of stealth units (MeOx and EtOx) and their distribution within the polymer chain on selected properties of polyplexes and describe characteristics of amino functionalized P(Ox)s in different cell lines. © 2018 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2018, 56, 1210–1224

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“…Some copolymerizations simply cannot be consistently controlled below, say, 5% conversion. Moreover, even at low conversion regions, there can be considerable composition drift which will also result in uncertainty, as clearly shown by Shawki et al in 1979 for the system in question. For medium and high conversion regions, the instantaneous ML equation should be integrated either analytically (Mayer‐Lowry model or numerically [direct numerical integration (DNI) model.…”

Section: Introductionmentioning

confidence: 93%

Optimal estimation of reactivity ratios for acrylamide/acrylic acid copolymerization

Riahinezhad

Kazemi

McManus

et al. 2013

J. Polym. Sci. Part A: Polym. Chem.

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Reactivity ratios for the important acrylamide (AAm)/acrylic acid (AAc) copolymerization system exhibit considerable scatter in previously published literature, and therefore, there is a need for more definitive values for these reactivity ratios. An appropriate methodology, based on the error‐in‐variables‐model (EVM) framework along with a direct numerical integration procedure, is applied in order to determine reliable reactivity ratios. The reliability of the results is confirmed with extensive and independent replication. Furthermore, via an EVM‐based criterion for the design of experiments using mechanistic models, optimal feed compositions are calculated, and from these optimal reactivity ratios are estimated for the first time (rAAm = 1.33 and rAAc = 0.23) based on information from the full conversion range. © 2013 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2013, 51, 4819–4827

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Estimation of the reactivity ratios in the copolymerization of acrylic acid and acrylamide from composition–conversion measurements by an improved nonlinear least-squares method

Cited by 40 publications

References 3 publications

Reactivity Ratio Estimation from Cumulative Copolymer Composition Data

Reactivity Ratio Estimation from Cumulative Copolymer Composition Data

Comparison of random and gradient amino functionalized poly(2‐oxazoline)s: Can the transfection efficiency be tuned by the macromolecular structure?

Optimal estimation of reactivity ratios for acrylamide/acrylic acid copolymerization

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