Evidence map›Paper›PMID 38475303›Full record

ReviewPolymers2024

NMR Analyses and Statistical Modeling of Biobased Polymer Microstructures-A Selected Review.

Huai N Cheng, Tetsuo Asakura, Koto Suganuma, Jose M Lagaron, Beatriz Melendez-Rodriguez, Atanu Biswas

Abstract readReview
In one paragraph

Review in Polymers, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Huai N ChengUSDA Agricultural Research Service, Southern Regional Research Center, New Orleans, LA 70124, USA.ORCID 0000-0001-8647-057X
Tetsuo AsakuraDepartment of Biotechnology, Tokyo University of Agriculture and Technology, Koganei, Tokyo 184-8588, Japan.ORCID 0000-0003-4472-6105
Koto SuganumaMaterial Analysis Research Center, Teijin Ltd., Hino, Tokyo 191-8512, Japan.
Jose M LagaronNovel Materials and Nanotechnology Group, IATA, CSIC, Av. Agustín Escardino 7, 46980 Paterna, Valencia, Spain.ORCID 0000-0002-0502-359X
Beatriz Melendez-RodriguezNovel Materials and Nanotechnology Group, IATA, CSIC, Av. Agustín Escardino 7, 46980 Paterna, Valencia, Spain.ORCID 0000-0002-2289-4098
Atanu BiswasUSDA Agricultural Research Service, National Center for Agricultural Utilization Research, Peoria, IL 61604, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

NMR analysis combined with statistical modeling offers a useful approach to investigate the microstructures of polymers. This article provides a selective review of the developments in both the NMR analysis of biobased polymers and the statistical models that can be used to characterize these materials. The information obtained from NMR and statistical models can provide insights into the microstructure and stereochemistry of appropriate biobased polymers and establish a systematic approach to their analysis. In suitable cases, the analysis can help optimize the synthetic procedures and facilitate the development of new or modified polymeric materials for various applications. Examples are given of the studies of poly(hydroxyalkanoates), poly(lactic acid), and selected polysaccharides, e.g., alginate, pectin, and chitosan. This article may serve as both a reference and a guide for future workers interested in the NMR sequence analysis of biobased materials.

Indexed as

alginatebiobased polymerschitosanNMRpectinpoly(hydroxyalkanoate)poly(lactic acid)sequence distributionstatistical modelingtacticity

Identifiers

PMID38475303
PMCPMC10934663

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.