Evidence map›Paper›PMID 36850215›Full record

ArticlePolymers2023

Variation in Abundance Ratio of Isoprene and Dipentene Produced from Wear Particles Composed of Natural Rubber by Pyrolysis Depending on the Particle Size and Thermal Aging.

Uiyeong Jung, Sung-Seen Choi

Open access · goldAbstract read
In one paragraph

Article in Polymers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.9field-weighted citation impact, top 32% of its field
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

0 citing papers in PubMed, 13 citations in OpenAlex.

No citing paper in PubMed yet.

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

2 authors at 1 institution in 1 country.

Uiyeong JungDepartment of Chemistry, Sejong University, 209 Neungdong-ro, Gwangjin-gu, Seoul 05006, Republic of Korea.
Sung-Seen ChoiDepartment of Chemistry, Sejong University, 209 Neungdong-ro, Gwangjin-gu, Seoul 05006, Republic of Korea.
Sejong University · KR

Funding

Ministry of Trade, Industry and Energy 20010851
6 · The paper itself

Abstract

Tire wear particles (TWPs) are generated by friction between the road and the tire. TWPs are one of the major microplastics found in environmental samples, such as road dust, particulate matter (PM), and sediment. TWP contents in environmental samples are generally analyzed using the pyrolysis technique. Tire tread compounds of heavy vehicles are usually composed of natural rubber (NR). Isoprene and dipentene are the principal pyrolysis products of NR, and dipentene is employed as the key marker for the determination of the TWP contents. In this study, an NR abrasion specimen was thermally aged, and an abrasion test was performed to obtain the wear particles. The influence of the wear particle size and thermal aging on the pyrolysis behavior of NR was investigated. The isoprene/dipentene ratio exponentially increased as the wear particle size decreased, and it was also increased by the thermal aging of the abrasion specimen. The increased isoprene/dipentene ratio by thermal aging was explained by increasing the crosslink density. Using the relationship between the wear particle size and the isoprene/dipentene ratio, it is possible to estimate the isoprene/dipentene ratio for very small TWP such as PM. The experimental results concluded that the wear particle size and thermal aging affect the formation of the key pyrogenic products, and the influencing factors should be considered for the quantification of TWP contents in the environmental samples.

Indexed as

crosslink densitynatural rubber (NR)pyrolysis behaviorthermal agingtire wear particle (TWP)wear particle size

Identifiers

PMID36850215
PMCPMC9967876
OpenAlexW4320497042

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.