Evidence map›Paper›PMID 38793147›Full record

ArticleMicromachines2024

Characterization of Sand and Dust Pollution Degradation Based on Sensitive Structure of Microelectromechanical System Flow Sensor.

Jinchuan Chen, Xiao Wen, Qinwen Huang, Wanchun Ren, Ruiwen Liu, Chunhua He

Abstract read
In one paragraph

Article in Micromachines, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Jinchuan ChenSchool of Information Engineering, Southwest University of Science and Technology (SWUST), 59 Qinglong Road, Mianyang 621010, China.
Xiao WenSchool of Information Engineering, Southwest University of Science and Technology (SWUST), 59 Qinglong Road, Mianyang 621010, China.
Qinwen HuangScience and Technology on Reliability Physics and Application Technology of Electronic Component Laboratory, China Electronic Product Reliability, and Environmental Testing Research Institute, Guangzhou 510610, China.
Wanchun RenSchool of Information Engineering, Southwest University of Science and Technology (SWUST), 59 Qinglong Road, Mianyang 621010, China.
Ruiwen LiuInstitute of Microelectronics Chinese Academy of Sciences, Beijing 100017, China.
Chunhua HeSchool of Computer, Guangdong University of Technology, Guangzhou 510006, China.ORCID 0000-0003-0826-3596

Funding

Basic and Applied Basic Research Project of Guangzhou Basic Research Program Grant No. 2023A04J1707Natural Science Foundation of Guangdong Province Grant No. 2023A1515010291the National Key R&D Program of China Grant number 2020YFB2008900the National Natural Science Foundation of China Grant No. 62104047
6 · The paper itself

Abstract

The effect of sand and dust pollution on the sensitive structures of flow sensors in microelectromechanical systems (MEMS) is a hot issue in current MEMS reliability research. However, previous studies on sand and dust contamination have only searched for sensor accuracy degradation due to heat conduction in sand and dust cover and have yet to search for other failure-inducing factors. This paper aims to discover the other inducing factors for the accuracy failure of MEMS flow sensors under sand and dust pollution by using a combined model simulation and sample test method. The accuracy of a flow sensor is mainly reflected by the size of its thermistor, so in this study, the output value of the thermistor value was chosen as an electrical characterization parameter to verify the change in the sensor's accuracy side by side. The results show that after excluding the influence of heat conduction, when sand particles fall on the device, the mutual friction between the sand particles will produce an electrostatic current; through the principle of electrostatic dissipation into the thermistor, the principle of measurement leads to the resistance value becoming smaller, and when the sand dust is stationary for some time, the resistance value returns to the expected level. This finding provides theoretical guidance for finding failure-inducing factors in MEMS failure modes.

Indexed as

electrostatic effectsfailure mechanismsmicroelectromechanical systemspredisposing factors

Identifiers

PMID38793147
PMCPMC11122801

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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.