Evidence map›Paper›PMID 35160852›Full record

ArticleMaterials (Basel, Switzerland)2022

Research on the Morphology Reconstruction of Deep Cryogenic Treatment on PtRu/nitrogen-Doped Graphene Composite Carbon Nanofibers.

Shuaishuai Lv, Yangyang Zhu, Xingxing Wang, Yu Zhu, Kaixuan Wang, Hongjun Ni, Ruobo Gu

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 2022. 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
–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

0 citing papers in PubMed.

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

7 authors.

Shuaishuai LvSchool of Mechanical Engineering, Nantong University, Nantong 226019, China.
Yangyang ZhuNantong Institute of Technology, Nantong 226019, China.
Xingxing WangSchool of Mechanical Engineering, Nantong University, Nantong 226019, China.ORCID 0000-0003-4437-5229
Yu ZhuSchool of Mechanical Engineering, Nantong University, Nantong 226019, China.
Kaixuan WangSchool of Mechanical Engineering, Nantong University, Nantong 226019, China.
Hongjun NiSchool of Mechanical Engineering, Nantong University, Nantong 226019, China.
Ruobo GuNantong Vocational College of Science & Technology, Nantong 226019, China.

Funding

A Priority Academic Program Development of Jiangsu Higher Education Institutions PAPDJiangsu Province Policy Guidance Program (International Science and Technology Cooperation) Project BZ2021045Nantong Applied Research Project, grant number JCZ21013 and JCZ21043
6 · The paper itself

Abstract

To improve the performance of PtRu/nitrogen-doped graphene composite carbon nanofibers, the composite carbon nanofibers were thermally compensated by deep cryogenic treatment (DCT), which realized the morphology reconstruction of composite carbon nanofibers. The effects of different DCT times were compared: 12 h, 18 h, and 24 h. The morphology reconstruction mechanism was explored by combining the change of inner chain structure and material group. The results showed that the fibers treated for 12 h had better physical and chemical properties, where the diameter is evenly distributed between 500 and 800 nm. Combined with Fourier infrared analysis, the longer the cryogenic time, the more easily the water vapor and nitrogen enter polymerization reaction, causing changes of chain structure and degradation performance. With great performance of carbonization and group transformation, the PtRu/nitrogen-doped graphene composite carbon nanofibers can be used as an efficient direct alcohol fuel cell catalyst and promote its commercialization.

Indexed as

composite carboncryogenic treatmentelectrospinningmorphology reconstruction

Identifiers

PMID35160852
PMCPMC8838454

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.