Evidence map›Paper›PMID 34945383›Full record

ArticleMicromachines2021

Acetone Sensor Based on FAIMS-MEMS.

Junna Zhang, Cheng Lei, Ting Liang, Ruifang Liu, Zhujie Zhao, Lei Qi, Abdul Ghaffar, Jijun Xiong

Abstract read
In one paragraph

Article in Micromachines, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

8 authors.

Junna ZhangState Key Laboratory of Dynamic Measurement Technology, North University of China, Taiyuan 030051, China.
Cheng LeiState Key Laboratory of Dynamic Measurement Technology, North University of China, Taiyuan 030051, China.
Ting LiangState Key Laboratory of Dynamic Measurement Technology, North University of China, Taiyuan 030051, China.
Ruifang LiuState Key Laboratory of Bioelectronics, Southeast University, Nanjing 210096, China.ORCID 0000-0001-5916-0533
Zhujie ZhaoState Key Laboratory of Dynamic Measurement Technology, North University of China, Taiyuan 030051, China.
Lei QiNorth Automatic Control Technology Institute, Taiyuan 030006, China.
Abdul GhaffarState Key Laboratory of Geomechanics and Geotechnical Engineering, Institute of Rock and Soil Mechanics, Chinese Academy of Sciences, Wuhan 430071, China.ORCID 0000-0001-8920-5034
Jijun XiongState Key Laboratory of Dynamic Measurement Technology, North University of China, Taiyuan 030051, China.

Funding

hanxi Province Key R&D Program Project 201903D121123Innovative Research Group Project of National Science Foundation 51821003the National Natural Science Foundation of China 51935011
6 · The paper itself

Abstract

In this paper, to address the problems of large blood draws, long testing times, and the inability to achieve dynamic detection of invasive testing for diabetes, stemming from the principle that type 1 diabetic patients exhale significantly higher levels of acetone than normal people, a FAIMS-MEMS gas sensor was designed to detect acetone, which utilizes the characteristics of high sensitivity, fast response, and non-invasive operation. It is prepared by MEMS processes, such as photolithography, etching, and sputtering, its specific dimensions are 4000 μm in length, 3000 μm in width and 800 μm in height and the related test system was built to detect acetone gas. The test results show that when acetone below 0.8 ppm is introduced, the voltage value detected by the sensor basically does not change, while when acetone gas exceeds 1.8 ppm, the voltage value detected by the sensor increases significantly. The detection accuracy of the sensor prepared by this method is about 0.02 ppm/mV, and the voltage change can reach 1 V with a response time of 3 s and a recovery time of 4 s when tested under 20 ppm acetone environment; this has good repeatability and stability, and has great prospects in the field of non-invasive detection of type 1 diabetes.

Indexed as

acetonediabetesFAIMS-MEMSreproducibilitystability

Identifiers

PMID34945383
PMCPMC8703384

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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.