Evidence map›Paper›PMID 36984993›Full record

ArticleMicromachines2023

Femtosecond Laser Processing Assisted SiC High-Temperature Pressure Sensor Fabrication and Performance Test.

You Zhao, Yulong Zhao, Lukang Wang, Yu Yang, Yabing Wang

Abstract read
In one paragraph

Article in Micromachines, 2023. 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. 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

5 authors.

You ZhaoState Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an 710049, China.
Yulong ZhaoState Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an 710049, China.
Lukang WangState Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an 710049, China.ORCID 0000-0002-5363-0140
Yu YangState Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an 710049, China.
Yabing WangState Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an 710049, China.

Funding

Key Research and Development Projects of Shaanxi Province of China 2020ZDLGY14-10the Postdoctoral Foundation of Shaanxi Province of China 2018BSHYDZZ06the Special Fund for Technology Innovation Guidance of Shaanxi Province of China 2019CGXNG-016
6 · The paper itself

Abstract

Due to material plastic deformation and current leakage at high temperatures, SOI (silicon-on-insulator) and SOS (silicon-on-sapphire) pressure sensors have difficulty working over 500 °C. Silicon carbide (SiC) is a promising sensor material to solve this problem because of its stable mechanical and electrical properties at high temperatures. However, SiC is difficult to process which hinders its application as a high-temperature pressure sensor. This study proposes a piezoresistive SiC pressure sensor fabrication method to overcome the difficulties in SiC processing, especially deep etching. The sensor was processed by a combination of ICP (inductive coupled plasma) dry etching, high-temperature rapid annealing and femtosecond laser deep etching. Static and dynamic calibration tests show that the accuracy error of the fabricated sensor can reach 0.33%FS, and the dynamic signal response time is 1.2 μs. High and low temperature test results show that the developed sensor is able to work at temperatures from -50 °C to 600 °C, which demonstrates the feasibility of the proposed sensor fabrication method.

Indexed as

fabrication methodfeasibilityhigh temperaturepressure sensorSiC

Identifiers

PMID36984993
PMCPMC10054109

What OpenQuestion holds

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LicenceCC BY
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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.