Evidence map›Paper›PMID 35889644›Full record

ArticleNanomaterials (Basel, Switzerland)2022

Pearson's Principle-Inspired Robust 2D Amorphous Ni-Fe-Co Ternary Hydroxides on Carbon Textile for High-Performance Electrocatalytic Water Splitting.

Rong Hu, Huiyu Jiang, Jinglin Xian, Shiyun Mi, Liyun Wei, Guangyu Fang, Jiayue Guo, Siqi Xu, Ziyang Liu, Huanyu Jin and 2 more

Abstract read
In one paragraph

Article in Nanomaterials (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

12 authors.

Rong HuState Key Laboratory of New Textile Materials and Advanced Processing Technologies, Hubei Key Laboratory of Biomass Fibers and Eco-Dyeing & Finishing, Wuhan Textile University, Wuhan 430200, China.
Huiyu JiangState Key Laboratory of New Textile Materials and Advanced Processing Technologies, Hubei Key Laboratory of Biomass Fibers and Eco-Dyeing & Finishing, Wuhan Textile University, Wuhan 430200, China.
Jinglin XianState Key Laboratory of New Textile Materials and Advanced Processing Technologies, Hubei Key Laboratory of Biomass Fibers and Eco-Dyeing & Finishing, Wuhan Textile University, Wuhan 430200, China.
Shiyun MiState Key Laboratory of New Textile Materials and Advanced Processing Technologies, Hubei Key Laboratory of Biomass Fibers and Eco-Dyeing & Finishing, Wuhan Textile University, Wuhan 430200, China.
Liyun WeiState Key Laboratory of New Textile Materials and Advanced Processing Technologies, Hubei Key Laboratory of Biomass Fibers and Eco-Dyeing & Finishing, Wuhan Textile University, Wuhan 430200, China.
Guangyu FangState Key Laboratory of New Textile Materials and Advanced Processing Technologies, Hubei Key Laboratory of Biomass Fibers and Eco-Dyeing & Finishing, Wuhan Textile University, Wuhan 430200, China.
Jiayue GuoState Key Laboratory of New Textile Materials and Advanced Processing Technologies, Hubei Key Laboratory of Biomass Fibers and Eco-Dyeing & Finishing, Wuhan Textile University, Wuhan 430200, China.
Siqi XuState Key Laboratory of New Textile Materials and Advanced Processing Technologies, Hubei Key Laboratory of Biomass Fibers and Eco-Dyeing & Finishing, Wuhan Textile University, Wuhan 430200, China.
Ziyang LiuState Key Laboratory of New Textile Materials and Advanced Processing Technologies, Hubei Key Laboratory of Biomass Fibers and Eco-Dyeing & Finishing, Wuhan Textile University, Wuhan 430200, China.
Huanyu JinInstitute for Sustainability, Energy and Resources, The University of Adelaide, Adelaide, SA 5005, Australia.ORCID 0000-0002-1950-2364
Huimin YuFuture Industries Institute, University of South Australia, Mawson Lakes Campus, Adelaide, SA 5095, Australia.
Jun WanState Key Laboratory of New Textile Materials and Advanced Processing Technologies, Hubei Key Laboratory of Biomass Fibers and Eco-Dyeing & Finishing, Wuhan Textile University, Wuhan 430200, China.ORCID 0000-0002-7575-7118

Funding

Natural Science Foundation of Hubei Province 2020CFB345Open Fund of Hubei Key Laboratory of Biomass Fiber and Ecological Dyeing and Finishing STRZ202119Open Fund of State Key Laboratory of New Textile Materials and Advanced Processing Technologies FZ2020001Young Talents Project of Hubei Education Department Q20201712
6 · The paper itself

Abstract

Layered double hydroxide (LDH) is widely used in electrocatalytic water splitting due to its good structural tunability, high intrinsic activity, and mild synthesis conditions, especially for flexible fiber-based catalysts. However, the poor stability of the interface between LDH and flexible carbon textile prepared by hydrothermal and electrodeposition methods greatly affects its active area and cyclic stability during deformation. Here, we report a salt-template-assisted method for the growth of two-dimensional (2D) amorphous ternary LDH based on dip-rolling technology. The robust and high-dimensional structure constructed by salt-template and fiber could achieve a carbon textile-based water splitting catalyst with high loading, strong catalytic activity, and good stability. The prepared 2D NiFeCo-LDH/CF electrode showed overpotentials of 220 mV and 151 mV in oxygen evolution and hydrogen evolution reactions, respectively, and simultaneously had no significant performance decrease after 100 consecutive bendings. This work provides a new strategy for efficiently designing robust, high-performance LDH on flexible fibers, which may have great potential in commercial applications.

Indexed as

amorphouselectrocatalytic water splittinglayered hydroxidePearson’s principleternary

Identifiers

PMID35889644
PMCPMC9316908

What OpenQuestion holds

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LicenceCC BY
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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.