Evidence map›Paper›PMID 35267769›Full record

ArticlePolymers2022

SI ATRP for the Surface Modifications of Optically Transparent Paper Films Made by TEMPO-Oxidized Cellulose Nanofibers.

Jem-Kun Chen, Hsiang-Ya Huang, Cheng-Wei Tu, Li-Ting Lee, Tongsai Jamnongkan, Chih-Feng Huang

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Polymers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed, 11 citations in OpenAlex.

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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

6 authors at 5 institutions in 2 countries.

Jem-Kun ChenDepartment of Materials Science and Engineering, National Taiwan University of Science and Technology, Taipei 10607, Taiwan.ORCID 0000-0003-3670-6710
Hsiang-Ya HuangDepartment of Chemical Engineering, i-Center for Advanced Science and Technology (iCAST), National Chung Hsing University, Taichung 40227, Taiwan.
Cheng-Wei TuIndustrial Technology Research Institute, Chutung, Hsinchu 31057, Taiwan.ORCID 0000-0003-3054-4546
Li-Ting LeeDepartment of Materials Science and Engineering, Feng Chia University, Taichung 40724, Taiwan.ORCID 0000-0002-5065-733X
Tongsai JamnongkanDepartment of Fundamental Science and Physical Education, Faculty of Science at Sriracha, Kasetsart University, Bangkok 10900, Thailand.ORCID 0000-0003-1431-3668
Chih-Feng HuangDepartment of Chemical Engineering, i-Center for Advanced Science and Technology (iCAST), National Chung Hsing University, Taichung 40227, Taiwan.ORCID 0000-0002-8062-8708
National Chung Hsing University · TWFeng Chia University · TWIndustrial Technology Research Institute · TWKasetsart University · THNational Taiwan University of Science and Technology · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Applications of cellulose nanofibers currently match the demands of biodegradable and renewable constituent biocomposites. In this study, we studied the process of preparing TEMPO-oxidized cellulose nanofibers (TOCNs). These nano-sized cellulose fibers (ca. 11 nm) can be fabricated to high transmittance and optically transparent paper (OP) films. Then the OP films can be facilely immobilized initiating sites for the subsequent surface-initiated atom transfer radical polymerization (SI ATRP). We investigated SI ATRP with styrene (St) kinetics and monitored chemical structure changes of the OP surfaces. The obtained OP-

Indexed as

optically transparent paper filmpolystyreneSI ATRPTOCN

Identifiers

PMID35267769
PMCPMC8912791
OpenAlexW4214680932

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.