A kinetic investigation of styrene/ethyl acrylate copolymerization

McManus, Neil T.; Penlidis, Alexander

doi:10.1002/(sici)1099-0518(19960130)34:2<237::aid-pola10>3.0.co;2-r

Cited by 28 publications

(38 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Another factor that should be considered is the feed compositions used to collect the experimental data (f1,0). The T-M criterion suggested f1,0 = 0.0788 and f1,0 = 0.7193, where monomer 1 is styrene [21]. While this is the statistically correct approach As shown in Figure 11, the reactivity ratio estimates are all similar for the copolymerization of styrene and ethyl acrylate, regardless of how many replicates are used (in this specific case, for this specific data set).…”

Section: Exhibit D: How Many Replicates Do We Really Need?mentioning

confidence: 86%

“…Many reactivity ratio estimation studies (including [18,[21][22][23]) have used the Tidwell-Mortimer (T-M) criterion for design of experiments to select the feed compositions at which to run copolymerizations for reactivity ratio estimation. In most cases, two optimal feed compositions (according to T-M) are used and replicated four times each.…”

Section: Exhibit D: How Many Replicates Do We Really Need?mentioning

confidence: 99%

“…In most cases, two optimal feed compositions (according to T-M) are used and replicated four times each. To establish the importance of replication and symmetry, this case study will analyze subsets of an original data set from the copolymerization of styrene (Sty; monomer 1) and ethyl acrylate (EA; monomer 2) [21].…”

Section: Exhibit D: How Many Replicates Do We Really Need?mentioning

confidence: 99%

“…Replication ensures that experimental results are repeatable, gives us an estimate of the experimental error and increases the degree of confidence in the resulting reactivity ratio estimates. The data reported by McManus and Penlidis [21] included an initial run and 3 replicates at two feed compositions (8 data points total); the data set is available in Appendix C, Section C.4.…”

Section: Exhibit D: How Many Replicates Do We Really Need?mentioning

confidence: 99%

“…Finally, only one data point at each feed composition was used in the analysis (black JCR and diamond point estimate; no replicates). To create this collection of reactivity ratio estimates and JCRs (Figure 11), the original data set [21] was revisited with the MATLAB-based RREVM program (blue JCR and circle point estimate in Figure 11; 3 replicates). Then, one randomly selected replicate at each feed composition was removed and the data was re-evaluated (red JCR and square point estimate; 2 replicates).…”

Section: Exhibit D: How Many Replicates Do We Really Need?mentioning

confidence: 99%

See 4 more Smart Citations

Computational Package for Copolymerization Reactivity Ratio Estimation: Improved Access to the Error-in-Variables-Model

Scott

Penlidis

2018

Processes

View full text Add to dashboard Cite

Abstract:The error-in-variables-model (EVM) is the most statistically correct non-linear parameter estimation technique for reactivity ratio estimation. However, many polymer researchers are unaware of the advantages of EVM and therefore still choose to use rather erroneous or approximate methods. The procedure is straightforward but it is often avoided because it is seen as mathematically and computationally intensive. Therefore, the goal of this work is to make EVM more accessible to all researchers through a series of focused case studies. All analyses employ a MATLAB-based computational package for copolymerization reactivity ratio estimation. The basis of the package is previous work in our group over many years. This version is an improvement, as it ensures wider compatibility and enhanced flexibility with respect to copolymerization parameter estimation scenarios that can be considered.

show abstract

Section: Exhibit D: How Many Replicates Do We Really Need?mentioning

confidence: 86%

Section: Exhibit D: How Many Replicates Do We Really Need?mentioning

confidence: 99%

Section: Exhibit D: How Many Replicates Do We Really Need?mentioning

confidence: 99%

Section: Exhibit D: How Many Replicates Do We Really Need?mentioning

confidence: 99%

Section: Exhibit D: How Many Replicates Do We Really Need?mentioning

confidence: 99%

See 3 more Smart Citations

Computational Package for Copolymerization Reactivity Ratio Estimation: Improved Access to the Error-in-Variables-Model

Scott

Penlidis

2018

Processes

View full text Add to dashboard Cite

show abstract

Copolymerization with depropagation: A study of ?-methyl styrene/methyl methacrylate in bulk at elevated temperatures

Palmer

McManus

Penlidis

2000

J. Polym. Sci. A Polym. Chem.

Self Cite

View full text Add to dashboard Cite

Previously published material on the α‐methyl styrene/methyl methacrylate (α‐MS/MMA) copolymer system at temperatures above the ceiling temperature of α‐MS has focused on low‐conversion results. Several attempts have been made to estimate copolymer reactivity ratios from experimental data, but in most cases errors are present in the determination of copolymer composition variables. In this article, the results of rigorous parameter estimations, as applied to two sets of equations developed independently by P. Wittmer (Adv Chem 1971, 99, 140–174) and H. Kruger, J. Bauer, and J. Rubner (Makromol Chem 1987, 188, 2163–2175), are discussed. Experimental data for the copolymer system at low conversions, as well as over the full conversion range, are presented, covering a temperature range of 60–140 °C. A comparison of the data trends with traditional copolymer systems indicates that the reversibility of both MMA and α‐MS must be considered when composition, polymerization rate, or molecular weight equations are being developed. © 2000 John Wiley & Sons, Inc. J Polym Sci A: Polym Chem 38: 1981–1990, 2000

show abstract

High temperature copolymerization of styrene/ethyl acrylate: Reactivity ratio estimation in bulk and solution

Sahloul¹,

Penlidis²

2004

Adv Polym Technol

View full text Add to dashboard Cite

Styrene/ethyl acrylate (Sty/EA) free-radical copolymerizations have been conducted in bulk with and without initiator and in solution using p-xylene and m-xylene (30 wt% and 60 wt% solvent level) at 100• C and 130• C. The monomer reactivity ratio values and their temperature dependence have been determined from low conversion copolymer composition data using the computer software package RREVM, which is based on the error in variables model (EVM) method. Copolymer composition data at low conversion confirmed the MayoLewis model at both temperatures. The reactivity ratio values of the Sty/EA system do not seem to change with dilution by nonpolar solvents at low concentration from the reactivity ratio values obtained in bulk with and without initiator. However, xylene isomers were found to have a slight effect on the reactivity ratio value of ethyl acrylate when high solvent concentration was utilized.

show abstract

A kinetic investigation of styrene/ethyl acrylate copolymerization

Cited by 28 publications

References 5 publications

Computational Package for Copolymerization Reactivity Ratio Estimation: Improved Access to the Error-in-Variables-Model

Computational Package for Copolymerization Reactivity Ratio Estimation: Improved Access to the Error-in-Variables-Model

Copolymerization with depropagation: A study of ?-methyl styrene/methyl methacrylate in bulk at elevated temperatures

High temperature copolymerization of styrene/ethyl acrylate: Reactivity ratio estimation in bulk and solution

Contact Info

Product

Resources

About