Evidence map›Paper›PMID 34912785›Full record

ArticleFrontiers in chemistry2021

Cu-Based Conductive MOF Grown

Qin Hu, Jie Qin, Xiao-Feng Wang, Guang-Ying Ran, Qiang Wang, Guang-Xiang Liu, Jian-Ping Ma, Jing-Yuan Ge, Hai-Ying Wang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in chemistry, 2021. 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
3.8field-weighted citation impact, top 6% 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

11 citing papers in PubMed, 56 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Review
  9. Article
  10. Article
  11. 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

9 authors at 5 institutions in 1 country.

Qin HuCollege of Chemistry and Materials Science, Sichuan Normal University, Chengdu, China.
Jie QinSchool of Life Sciences and Medicine, Shandong University of Technology, Zibo, China.
Xiao-Feng WangSchool of Environmental Science, Nanjing Xiaozhuang University, Nanjing, China.
Guang-Ying RanCollege of Chemistry and Materials Science, Sichuan Normal University, Chengdu, China.
Qiang WangCollege of Chemistry and Materials Science, Sichuan Normal University, Chengdu, China.
Guang-Xiang LiuSchool of Environmental Science, Nanjing Xiaozhuang University, Nanjing, China.
Jian-Ping MaSchool of Chemistry, Chemical Engineering and Materials Science, Shandong Normal University, Jinan, China.
Jing-Yuan GeCollege of Chemistry and Materials Engineering, Wenzhou University, Wenzhou, China.
Hai-Ying WangCollege of Chemistry and Materials Science, Sichuan Normal University, Chengdu, China.
Sichuan Normal University · CNNanjing Xiaozhuang University · CNShandong Normal University · CNShandong University of Technology · CNWenzhou University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A non-enzymatic electrochemical sensor for glucose detection is executed by using a conductive metal-organic framework (MOF) Cu-MOF, which is built from the 2,3,6,7,10,11-hexahydroxytriphenylene (HHTP) ligand and copper acetate by hydrothermal reaction. The Cu-MOF demonstrates superior electrocatalytic activity for glucose oxidation under alkaline pH conditions. As an excellent non-enzymatic sensor, the Cu-MOF grown on Cu foam (Cu-MOF/CF) displays an ultra-low detection limit of 0.076 μM through a wide concentration range (0.001-0.95 mM) and a strong sensitivity of 30,030 mA μM

Indexed as

electrochemical sensorglucoseMOFnon-enzymaticredox activity

Identifiers

PMID34912785
PMCPMC8666423
OpenAlexW3215037570

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.