Evidence map›Paper›PMID 40808154›Full record

ArticlePolymers2025

Evaluation of Polypropylene Reusability Using a Simple Mechanical Model Derived from Injection-Molded Products.

Tetsuo Takayama, Rikuto Takahashi, Nao Konno, Noriyuki Sato

Abstract read
In one paragraph

Article in Polymers, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
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

4 authors.

Tetsuo TakayamaGraduate School of Organic Materials Science, Yamagata University, Yamagata 990-8510, Japan.ORCID 0000-0002-5170-8346
Rikuto TakahashiDepartment of Polymeric and Organic Materials Engineering, Yamagata University, Yamagata 990-8510, Japan.
Nao KonnoIndustrial Technology Institute, Miyagi Prefectural Government, Miyagi 981-3206, Japan.
Noriyuki SatoIndustrial Technology Institute, Miyagi Prefectural Government, Miyagi 981-3206, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In response to growing global concerns about plastic waste, the development of efficient recycling technologies for thermoplastics has become increasingly important. Polypropylene (PP), a widely used commodity resin, is of particular interest because of the urgent need to establish sustainable material circulation. However, conventional mechanical property evaluations of injection-molded products typically require dedicated specimens, which involve additional material and energy costs. As described herein, we propose a simplified mechanical model to derive Poisson's ratio and critical expansion stress directly from standard uniaxial tensile tests of molded thermoplastics. The method based on the true stress-true strain relationship in the small deformation region was validated using various thermoplastics (PP, POM, PC, and ABS), with results showing good agreement with those of the existing literature. The model was applied further to assess changes in mechanical properties of Homo-PP and Block-PP subjected to repeated extrusion. Both materials exhibited reductions in elastic modulus and critical expansion stress with increasing extrusion cycles, whereas Block-PP showed a slower degradation rate because of thermo-crosslinking in its ethylene-propylene rubber (EPR) phase. DSC and chemiluminescence analyses suggested changes in stereoregularity and radical formation as key factors. This method offers a practical approach for evaluating recycled PP and contributes to high-quality recycling and material design.

Indexed as

isotacticitymechanical propertiesPoisson’s ratio

Identifiers

PMID40808154
PMCPMC12349465

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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.