Evidence map›Paper›PMID 35957055›Full record

ArticleNanomaterials (Basel, Switzerland)2022

Graphene-Based Ion-Selective Field-Effect Transistor for Sodium Sensing.

Ting Huang, Kan Kan Yeung, Jingwei Li, Honglin Sun, Md Masruck Alam, Zhaoli Gao

Open access · goldAbstract 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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
2.1field-weighted citation impact, top 13% 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

3 citing papers in PubMed, 15 citations in OpenAlex.

  1. Article
  2. Review
  3. Graphene for Electronics.Nanomaterials (Basel, Switzerland) · 2022
    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

6 authors at 1 institution in 1 country.

Ting HuangBiomedical Engineering Department, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China.
Kan Kan YeungBiomedical Engineering Department, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China.ORCID 0000-0001-5357-8808
Jingwei LiBiomedical Engineering Department, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China.
Honglin SunBiomedical Engineering Department, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China.
Md Masruck AlamBiomedical Engineering Department, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China.ORCID 0000-0003-4063-8992
Zhaoli GaoBiomedical Engineering Department, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China.
Chinese University of Hong Kong · HK

Funding

the Key-Area Research and Development Program of Guangdong Province Grant No. 2020B0101030002the National Natural Science Foundation of China Project No. 62101475the Research Grant Council of Hong Kong Project No. 24201020 and 14207421the Research Matching Grant Scheme of Hong Kong Government Project No. 8601547
6 · The paper itself

Abstract

Field-effect transistors have attracted significant attention in chemical sensing and clinical diagnosis, due to their high sensitivity and label-free operation. Through a scalable photolithographic process in this study, we fabricated graphene-based ion-sensitive field-effect transistor (ISFET) arrays that can continuously monitor sodium ions in real-time. As the sodium ion concentration increased, the current-gate voltage characteristic curves shifted towards the negative direction, showing that sodium ions were captured and could be detected over a wide concentration range, from 10

Indexed as

grapheneion-selective field-effect transistorreal-time monitoringsodium ions

Identifiers

PMID35957055
PMCPMC9370261
OpenAlexW4289205462

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.