On estimating reactivity ratios using the integrated mayo–lewis equation

Plaumann, Heinz; Branston, Randolph E.

doi:10.1002/pola.1989.080270827

Cited by 8 publications

(10 citation statements)

References 9 publications

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“…The figure indicates that ⌬f is maximized at values of f 0 ϭ 0.17 and 0.78, close to the results obtained by previous simulations 25 (0.19 and 0.76). Plaumann and Brandston 30 noticed that when using the integrated form of the copolymerization equation, a minimum of two experiments should be performed, at different initial fractions. They indicated initial fractions of f 0 ϭ 0.20 and 0.80, based on "a pragmatic approach" to use a pair of initial feed compositions which are "far apart".…”

Section: Raman Resultsmentioning

confidence: 99%

“…30 The fact that the confidence intervals are stretched indicates that there exists a correlation between the two reactivity ratios. This correlation depends on the initial fraction which is chosen for the experiment, indicated by the different directions of the JCIs.…”

Section: Analysis Of the Individual Experimentsmentioning

confidence: 98%

“…25,30 From a statistician's point of view, the best way to combine the data sets is a weighting scheme by directly adding the absolute sum of the squared residual (weighted) errors (SRE) for each pair of reactivity ratios. However, from the experimentalist's point of view, this weighting scheme may have some drawbacks.…”

Section: Analysis Of Combined Experimentsmentioning

confidence: 99%

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Nonlinear regression by visualization of the sum of residual space applied to the integrated copolymerization equation with errors in all variables. II. Application to the system methyl methacrylate-?-methylene-?-butyrolactone using on-line Raman spectroscopy

Brink

Smulders

Herk

et al. 1999

J. Polym. Sci. A Polym. Chem.

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The copolymerization of α‐methylene‐γ‐butyrolactone and methyl methacrylate in DMSO was studied by on‐line Raman spectroscopy. Reactivity ratios for this system were estimated from the in situ conversion measurements. The estimates are in good agreement with estimates obtained from low‐conversion experiments where the composition of the copolymer was analyzed by 1H‐NMR. In order to obtain reliable estimates from the Raman data in combination with the integrated copolymerization equation, at least two experiments starting from different initial monomer feed fractions should be conducted. © 1999 John Wiley & Sons, Inc. J Polym Sci A: Polym Chem 37: 3804–3816, 1999

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Section: Raman Resultsmentioning

confidence: 99%

Section: Analysis Of the Individual Experimentsmentioning

confidence: 98%

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Nonlinear regression by visualization of the sum of residual space applied to the integrated copolymerization equation with errors in all variables. II. Application to the system methyl methacrylate-?-methylene-?-butyrolactone using on-line Raman spectroscopy

Brink

Smulders

Herk

et al. 1999

J. Polym. Sci. A Polym. Chem.

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“…Thus, with copolymer compositions obtained using different feed ratios, one may estimate the two reactivity ratios via nonlinear fitting of the parameters in eq 7. As for this, attention has to be paid in choosing the appropriate set of feed conditions, 20 and to the nonlinear fitting approach employed to avoid artifacts. 21…”

Section: Nmr Analysismentioning

confidence: 99%

On the origin and consequences of high DMAEMA reactivity ratio in ATRP copolymerization with MMA: An experimental and theoretical study^#

Mella

Rocca

Miele

et al. 2018

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

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Designing and tuning a copolymerization process to obtain specific material properties is still fundamentally empirical and requires the determination of apparent reactivity ratios rs. To this end, PEG–(MMA–DMAEMA)n copolymers obtained via ATRP of MMA and DMAEMA using a PEG‐based initiator in toluene were analyzed to extract monomer relative reactivities; the impact of changing solvent on the latter was also tested. Differing from previous free radical and controlled radical copolymerizations (CRcoP), we found that DMAEMA is preferentially included (rMMAnormals=0.36(±10%) and rDMAEMAnormals=2.76(±15%)) in toluene; increasing the solvent polarity decreased the gap between rs. With these data, kMC simulations based on the copolymerization terminal model were used to investigate copolymer microstructure, which is not amenable to NMR investigation. kMC simulations evidenced both a gradient‐like nature of the copolymers and a somewhat unexpected qualitative change in the probability of finding MMA‐rich triads along the chain depending on initial feed composition. An additional DFT analysis suggested the likely formation of a DMAEMA:CuBr:2‐2′‐bipyridine complex, which being involved in the regeneration of reactive radicals from dormant species, is expected to locally increase DMAEMA concentration favoring its addition to the growing chains. The formation of such complex is also supported by 1H‐NMR experiments. © 2018 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2018, 56, 1366–1382

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“…Numerous reports are available [19,[229][230][231][232][233][234][235][236][237][238][239][240][241][242][243][244][245][246][247][248] on the development and analysis of the different procedures of estimating the reactivity ratio from the experimental data obtained over a wide range of conversions. These procedures employ different modifications of the integrated form of the copolymerization equation.…”

Section: Reactivity Ratios Estimation Based On Copolymer Composition mentioning

confidence: 99%

Modern aspects of quantitative theory of free-radical copolymerization

Кучанов

Free Radical Copolimerization Dispersions Glassy State Relaxation

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On estimating reactivity ratios using the integrated mayo–lewis equation

Cited by 8 publications

References 9 publications

Nonlinear regression by visualization of the sum of residual space applied to the integrated copolymerization equation with errors in all variables. II. Application to the system methyl methacrylate-?-methylene-?-butyrolactone using on-line Raman spectroscopy

Nonlinear regression by visualization of the sum of residual space applied to the integrated copolymerization equation with errors in all variables. II. Application to the system methyl methacrylate-?-methylene-?-butyrolactone using on-line Raman spectroscopy

On the origin and consequences of high DMAEMA reactivity ratio in ATRP copolymerization with MMA: An experimental and theoretical study^#

Modern aspects of quantitative theory of free-radical copolymerization

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On estimating reactivity ratios using the integrated mayo–lewis equation

Cited by 8 publications

References 9 publications

Nonlinear regression by visualization of the sum of residual space applied to the integrated copolymerization equation with errors in all variables. II. Application to the system methyl methacrylate-?-methylene-?-butyrolactone using on-line Raman spectroscopy

Nonlinear regression by visualization of the sum of residual space applied to the integrated copolymerization equation with errors in all variables. II. Application to the system methyl methacrylate-?-methylene-?-butyrolactone using on-line Raman spectroscopy

On the origin and consequences of high DMAEMA reactivity ratio in ATRP copolymerization with MMA: An experimental and theoretical study#

Modern aspects of quantitative theory of free-radical copolymerization

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Product

Resources

About

On the origin and consequences of high DMAEMA reactivity ratio in ATRP copolymerization with MMA: An experimental and theoretical study^#