Evidence map›Paper›PMID 37201104›Full record

ArticleMicrosystems & nanoengineering2023

Frequency unlocking-based MEMS bifurcation sensors.

Yan Qiao, Zhan Shi, Yutao Xu, Xueyong Wei, Alaaeldin Elhady, Eihab Abdel-Rahman, Ronghua Huan, Wenming Zhang

Open access · goldAbstract read
In one paragraph

Article in Microsystems & nanoengineering, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
4.5field-weighted citation impact, top 5% 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

6 citing papers in PubMed, 22 citations in OpenAlex.

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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 at 4 institutions in 2 countries.

Yan Qiao *State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China.
Zhan Shi *Department of Mechanics, Key Laboratory of Soft Machines and Smart Devices of Zhejiang Province, Zhejiang University, Hangzhou, China.
Yutao XuState Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an, China.
Xueyong WeiState Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an, China.ORCID 0000-0002-6443-4727
Alaaeldin ElhadyDepartment of Systems Design Engineering, University of Waterloo, Waterloo, ON Canada.ORCID 0000-0002-6963-8462
Eihab Abdel-RahmanDepartment of Systems Design Engineering, University of Waterloo, Waterloo, ON Canada.
Ronghua HuanDepartment of Mechanics, Key Laboratory of Soft Machines and Smart Devices of Zhejiang Province, Zhejiang University, Hangzhou, China.
Wenming ZhangState Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China.ORCID 0000-0001-6743-1006
Shanghai Jiao Tong University · CNUniversity of Waterloo · CAXi'an Jiaotong University · CNZhejiang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

MEMS resonators exhibit rich dynamic behaviors under the internal resonance regime. In this work, we present a novel MEMS bifurcation sensor that exploits frequency unlocking due to a 1:3 internal resonance between two electrostatically coupled micro-resonators. The proposed detection mechanism allows the sensor to operate in binary (digital) and analog modes, depending on whether the sensor merely detects a significant jump event in the peak frequency upon unlocking or measures the shift in the peak frequency after unlocking and uses it in conjunction with a calibration curve to estimate the corresponding change in stimulus. We validate the success of this sensor paradigm by experimentally demonstrating charge detection. High charge resolutions are achieved in binary mode, up to 0.137 fC, and in analog mode, up to 0.01 fC. The proposed binary sensor enables extraordinarily high detection resolutions due to the excellent frequency stability under internal resonance and the high signal-to-noise ratio of the shift in peak frequency. Our findings offer new opportunities for high-performance ultrasensitive sensors.

Indexed as

Electrical and electronic engineeringEngineering

Identifiers

PMID37201104
PMCPMC10185684
OpenAlexW4376601606

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.