Evidence map›Paper›PMID 30997590›Full record

ArticleNanoscale research letters2019

A Simple Electrochemical Route to Access Amorphous Co-Ni Hydroxide for Non-enzymatic Glucose Sensing.

Hongbo Li, Ling Zhang, Yiwu Mao, Chengwei Wen, Peng Zhao

Abstract read
In one paragraph

Article in Nanoscale research letters, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. F-doped KMnRSC advances · 2026
    Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. HNanomaterials (Basel, Switzerland) · 2022
    Article
  8. Review
  9. Article
  10. Enzyme-Free Glucose Biosensors Based on MoSNanoscale research letters · 2020
    Review
  11. 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

5 authors.

Hongbo LiInstitute of Nuclear Physics and Chemistry (INPC), China Academy of Engineering Physics (CAEP), Mianyang, 621999, People's Republic of China.
Ling ZhangInstitute of Nuclear Physics and Chemistry (INPC), China Academy of Engineering Physics (CAEP), Mianyang, 621999, People's Republic of China.
Yiwu MaoInstitute of Nuclear Physics and Chemistry (INPC), China Academy of Engineering Physics (CAEP), Mianyang, 621999, People's Republic of China.
Chengwei WenInstitute of Nuclear Physics and Chemistry (INPC), China Academy of Engineering Physics (CAEP), Mianyang, 621999, People's Republic of China.
Peng ZhaoInstitute of Nuclear Physics and Chemistry (INPC), China Academy of Engineering Physics (CAEP), Mianyang, 621999, People's Republic of China. zhaopeng2021@126.com.ORCID http://orcid.org/0000-0002-7782-2446

Funding

National Natural Science Foundation of China 51602294Science and Technology Foundation of China Academy Engineering 2015B0302047
6 · The paper itself

Abstract

Among the numerous transition metal hydroxide materials, cobalt- and nickel-based hydroxides have been extensively studied for their excellent electrochemical performances such as non-enzymatic electrochemical sensors. Binary cobalt-nickel hydroxide has received extensive attention for its exceptionally splendid electrochemical behaviors as a promising glucose sensor material. In this work, we report the synthesis of three-dimensional amorphous Co-Ni hydroxide nanostructures with homogeneous distribution of elements via a simple and chemically clean electrochemical deposition method. The amorphous Co-Ni hydroxide, as a non-enzymatic glucose sensor material, exhibits a superior biosensing performance toward glucose detection for its superior electron transfer capability, high specific surface area, and abundant intrinsic redox couples of Ni

Indexed as

AmorphousCo-Ni hydroxideGlucose sensorNon-enzymatic

Identifiers

PMID30997590
PMCPMC6470241

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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.