Evidence map›Paper›PMID 38318078›Full record

ArticleHeliyon2024

Thermal, thermomechanical and structural properties of recycled polyethylene terephthalate (rPET)/waste marble dust composites.

László Lendvai, Tej Singh, Ferenc Ronkay

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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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

5 citing papers in PubMed.

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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

3 authors.

László LendvaiDepartment of Materials Science and Engineering, Széchenyi István University, H-9026, Győr, Hungary.
Tej SinghSavaria Institute of Technology, Faculty of Informatics, ELTE Eötvös Loránd University, Budapest, 1117, Hungary.
Ferenc RonkayDepartment of Innovative Vehicles and Materials, GAMF Faculty of Engineering and Computer Science, John von Neumann University, H-6000, Kecskemét, Hungary.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The main objective of this work is to review the capability of using waste marble dust (MD) particles as reinforcing materials in recycled polymeric composites to achieve environmentally friendly materials. In the present study, polymer composites were fabricated from recycled polyethylene terephthalate (rPET) and MD and then analyzed for their structural and thermal properties. Preparation of rPET-based composites containing 0-20 wt% MD was carried out through extrusion and injection molding. For their characterization Fourier transform infrared spectroscopy (FTIR), differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), and dynamic mechanical analysis (DMA) were applied. The DSC analysis revealed a nucleating effect of MD on rPET, which was manifested in a higher crystallization temperature (196.7 °C ⇒ 204.4 °C); however, the marble particles were also found to hamper chain mobility, thereby decreasing the crystallinity ratio (23.7 % ⇒ 19.2 %) of rPET and altering its crystalline structure. According to the TGA measurements, a slight increase occurred in the thermal stability of rPET, its major decomposition temperature increased from 446 °C to 451 °C when 20 wt% MD was incorporated into it. DMA showed an improved stiffness in the entire investigated temperature range for MD-filled composites versus neat rPET. Additionally, several factors were derived from the DMA data, including the effectiveness factor, degree of entanglement, and reinforcing efficiency factor which all suggested a decent interaction between the components indicating a proper reinforcing ability of marble powder. However, above 5 wt% MD content the reinforcing efficiency deteriorated due to the agglomeration of filler particles, which was also supported by scanning electron microscopic images.

Indexed as

CompositesMarble dustRecycled polyethylene terephthalaterPETThermal properties

Identifiers

PMID38318078
PMCPMC10839988

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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.