Evidence map›Paper›PMID 31592481›Full record

ArticleACS omega2019

A Simple and Scalable Approach To Remarkably Boost the Overall Water Splitting Activity of Stainless Steel Electrocatalysts.

Yingxia Gao, Tuzhi Xiong, Ya Li, Yongchao Huang, Yuping Li, M-Sadeeq Jie Tang Balogun

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in ACS omega, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Review
  6. N-doped carbon anchored CoSFrontiers of optoelectronics · 2022
    Article
  7. Review
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.

Yingxia GaoCollege of Materials Science and Engineering, Hunan University, Changsha 410082, Hunan, People's Republic of China.
Tuzhi XiongCollege of Materials Science and Engineering, Hunan University, Changsha 410082, Hunan, People's Republic of China.
Ya LiInstitute of Environmental Research at Greater Bay, Key Laboratory for Water Quality and Conservation of the Pearl River Delta, Ministry of Education, Guangzhou University, Guangzhou 510006, People's Republic of China.
Yongchao HuangInstitute of Environmental Research at Greater Bay, Key Laboratory for Water Quality and Conservation of the Pearl River Delta, Ministry of Education, Guangzhou University, Guangzhou 510006, People's Republic of China.
Yuping LiCollege of Materials Science and Engineering, Hunan University, Changsha 410082, Hunan, People's Republic of China.
M-Sadeeq Jie Tang BalogunCollege of Materials Science and Engineering, Hunan University, Changsha 410082, Hunan, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The stainless steel mesh (SSM) has received growing consideration as an electrocatalyst for efficient hydrogen and oxygen evolution reactions. Recently, the application of SSM as an oxygen evolution reaction (OER) electrocatalyst has been more promising, while its hydrogen evolution reaction (HER) catalytic activity is very low, which definitely affects its overall water splitting activity. Herein, a simple chemical bath deposition (CBD) method followed by phosphorization is employed to significantly boost the overall water splitting performance of SSM. The CBD method could allow the voids between the SSM fibers to be filled with Ni and P. Electrocatalytic studies show that the CBD-treated and phosphorized stainless steel (denoted SSM-Ni-P) exhibits an HER overpotential of 149 mV, while the phosphorization-free CBD-treated SSM (denoted as SSM-Ni) delivers an OER overpotential of 223 mV, both at a current density of 10 mA cm

Identifiers

PMID31592481
PMCPMC6777119

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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.