Evidence map›Paper›PMID 30948705›Full record

ArticleNature communications2019

Free radical sensors based on inner-cutting graphene field-effect transistors.

Zhen Wang, Kongyang Yi, Qiuyuan Lin, Lei Yang, Xiaosong Chen, Hui Chen, Yunqi Liu, Dacheng Wei

Abstract read
In one paragraph

Article in Nature communications, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing 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

26 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Recent Advances in Xenes Based FET for Biosensing Applications.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Recent progress on rapid diagnosis of COVID-19 by point-of-care testing platforms.Chinese chemical letters = Zhongguo hua xue kuai bao · 2023
    Review
  12. Review
  13. Review
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Review
  20. 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

8 authors.

Zhen WangState Key Laboratory of Molecular Engineering of Polymers, Fudan University, 200433, Shanghai, China.
Kongyang YiState Key Laboratory of Molecular Engineering of Polymers, Fudan University, 200433, Shanghai, China.ORCID http://orcid.org/0000-0002-1941-1032
Qiuyuan LinDepartment of Chemistry, Fudan University, 200433, Shanghai, China.
Lei YangState Key Laboratory of Molecular Engineering of Polymers, Fudan University, 200433, Shanghai, China.
Xiaosong ChenState Key Laboratory of Molecular Engineering of Polymers, Fudan University, 200433, Shanghai, China.
Hui ChenDepartment of Chemistry, Fudan University, 200433, Shanghai, China.
Yunqi LiuInstitute of Molecular Materials and Devices, Fudan University, 200433, Shanghai, China.
Dacheng WeiState Key Laboratory of Molecular Engineering of Polymers, Fudan University, 200433, Shanghai, China. weidc@fudan.edu.cn.ORCID http://orcid.org/0000-0003-3593-9897

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Due to ultra-high reactivity, direct determination of free radicals, especially hydroxyl radical (•OH) with ultra-short lifetime, by field-effect transistor (FET) sensors remains a challenge, which hampers evaluating the role that free radical plays in physiological and pathological processes. Here, we develop a •OH FET sensor with a graphene channel functionalized by metal ion indicators. At the electrolyte/graphene interface, highly reactive •OH cuts the cysteamine to release the metal ions, resulting in surface charge de-doping and a current response. By this inner-cutting strategy, the •OH is selectively detected with a concentration down to 10

Identifiers

PMID30948705
PMCPMC6449349

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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.