1995
DOI: 10.1002/pola.1995.080330205
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Molecular weight distributions of linear polymers: Detailed analysis from GPC data

Abstract: The GPC method is used widely to measure molecular weights of linear polymers. High‐quality GPC data contains detailed information on many aspects of the polymer's molecular weight distribution (MWD). This information can be extracted from the data using computer analysis. Equations have been derived for the two simplest MWD functions in the GPC coordinates: the Flory function (one growing polymer chain produces one polymer molecule), and for the case when two polymer radicals combine into one polymer molecule… Show more

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Cited by 117 publications
(138 citation statements)
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References 23 publications
(5 reference statements)
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“…Corresponding GPC curves/data are obtained. However, the results obtained by extracting MWD information from the GPC curves according to Kission' approach 29 are similar. In our previous work, 25 we recorded the polymerization kinetic data under the same experimental conditions as those in this work except the atomic ratio of Si/Al.…”
Section: Deconvolution Of Mwd Datamentioning
confidence: 63%
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“…Corresponding GPC curves/data are obtained. However, the results obtained by extracting MWD information from the GPC curves according to Kission' approach 29 are similar. In our previous work, 25 we recorded the polymerization kinetic data under the same experimental conditions as those in this work except the atomic ratio of Si/Al.…”
Section: Deconvolution Of Mwd Datamentioning
confidence: 63%
“…In practice, Kission' s approach is the resolution of GPC curves using the Flory distribution equation. 29 This algorithm assumed that each site type produces a most-probable MWD,…”
Section: Deconvolution Of Mwd Datamentioning
confidence: 99%
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“…It seemed that the MWD curve was piled up by MWD curves of polymers produced by different types of active centers (as shown in Fig. 1), which could be mathematically expressed as follows [31]:…”
Section: Gel-permeation Chromatography (Gpc) and 13 C-nmr Analysismentioning
confidence: 99%