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Cited by 227

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Crystallization analysis fractionation: A new technique for the analysis of branching distribution in polyolefins

Monrabal, Benjamin·1994·Journal of Applied Polymer Science

Abstract

A new technique to analyze the short‐chain branching distribution (SCBD) in linear lowdensity polyethylene has been developed. The technique referred as crystallization analysis fractionation is based on a stepwise precipitation approach. By monitoring the polymer solution concentration during crystallization, the cumulative and differential SCBD can be obtained without the need of physical separation of fractions. The new technique has been shown to provide similar results to temperature rising elution fractionation but in a shorter time and with a simplified apparatus. It allows the simultaneous analysis of various samples and could also be used for analysis of polypropylene and other semicrystalline polymers that can be fractionated on the basis of crystallizability. © 1994 John Wiley & Sons, Inc.

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Crossref · 10.1002/app.1994.070520403

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Metadata

Authors
Monrabal, B.
Venue
Journal of Applied Polymer Science
Publisher
Wiley
Published
1994-04-25
Volume
52
Issue
4
Pages
491-499
ISSN
  • 0021-8995 (ISSN-L)
  • 1097-4628
OpenAlex
W1967623307
Cited by
227
References
1
FWCI
2.02
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Crystallization analysis fractionation: A new technique for the analysis of branching distribution in polyolefins. https://app.cochat.ai/papers/10.1002/app.1994.070520403
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Monrabal, B. (1994). Crystallization analysis fractionation: A new technique for the analysis of branching distribution in polyolefins. Journal of Applied Polymer Science. https://doi.org/10.1002/app.1994.070520403

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.