Evidence map›Paper›PMID 34300642›Full record

ArticleSensors (Basel, Switzerland)2021

Effects of Buffer Concentration on the Sensitivity of Silicon Nanobelt Field-Effect Transistor Sensors.

Chi-Chang Wu, Min-Rong Wang

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.6field-weighted citation impact, top 37% 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

4 citing papers in PubMed, 8 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. 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

2 authors at 2 institutions in 1 country.

Chi-Chang WuDepartment of Electronic Engineering, National Chin-Yi University of Technology, Taichung 411030, Taiwan.ORCID 0000-0002-3013-8401
Min-Rong WangDepartment of Electronic Engineering, Feng Chia University, Taichung 407802, Taiwan.
Feng Chia University · TWNational Chin-Yi University of Technology · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this work, a single-crystalline silicon nanobelt field-effect transistor (SiNB FET) device was developed and applied to pH and biomolecule sensing. The nanobelt was formed using a local oxidation of silicon technique, which is a self-aligned, self-shrinking process that reduces the cost of production. We demonstrated the effect of buffer concentration on the sensitivity and stability of the SiNB FET sensor by varying the buffer concentrations to detect solution pH and alpha fetoprotein (AFP). The SiNB FET sensor was used to detect a solution pH ranging from 6.4 to 7.4; the response current decreased stepwise as the pH value increased. The stability of the sensor was examined through cyclical detection under solutions with different pH; the results were stable and reliable. A buffer solution of varying concentrations was employed to inspect the sensing capability of the SiNB FET sensor device, with the results indicating that the sensitivity of the sensor was negatively dependent on the buffer concentration. For biomolecule sensing, AFP was sensed to test the sensitivity of the SiNB FET sensor. The effectiveness of surface functionalization affected the AFP sensing result, and the current shift was strongly dependent on the buffer concentration. The obtained results demonstrated that buffer concentration plays a crucial role in terms of the sensitivity and stability of the SiNB FET device in chemical and biomolecular sensing.

Indexed as

Biosensing TechniquesSiliconTransistors, ElectronicSiliconalpha fetoproteinDebye screening lengthFET sensorionic strengthpH sensingsilicon nanobelt

Identifiers

PMID34300642
PMCPMC8309807
OpenAlexW3185536851

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.