Evidence map›Paper›PMID 30424448›Full record

ArticleMicromachines2018

Ultrahigh Frequency Ultrasonic Transducers Design with Low Noise Amplifier Integrated Circuit.

Di Li, Chunlong Fei, Qidong Zhang, Yani Li, Yintang Yang, Qifa Zhou

Abstract read
In one paragraph

Article in Micromachines, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Review
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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

6 authors.

Di LiSchool of Microelectronics, Xidian University, Xi'an 710071, China. lidi2004@126.com.ORCID 0000-0001-6118-7401
Chunlong FeiSchool of Microelectronics, Xidian University, Xi'an 710071, China. clfei@xidian.edu.cn.
Qidong ZhangSchool of Microelectronics, Xidian University, Xi'an 710071, China. qdzhang@xidian.edu.cn.
Yani LiSchool of Microelectronics, Xidian University, Xi'an 710071, China. yanili@mail.xidian.edu.cn.
Yintang YangSchool of Microelectronics, Xidian University, Xi'an 710071, China. ytyang@xidian.edu.cn.
Qifa ZhouDepartment of Ophthalmology and Biomedical Engineering, University of Southern California, Los Angeles, CA 90089-1111, USA. qifazhou@usc.edu.

Funding

National Key Project of Intergovernmental Cooperation in International Scientific and Technological Innovation 2016YFE0107900National Natural Science Foundation of China No.11604251National Natural Science Foundation of China No. 61504102Natural Science Foundations of Shannxi Province 2017JQ1006Xidian University fundings JBG161101Xidian University fundings XJS16034
6 · The paper itself

Abstract

This paper describes the design of an ultrahigh frequency ultrasound system combined with tightly focused 500 MHz ultrasonic transducers and high frequency wideband low noise amplifier (LNA) integrated circuit (IC) model design. The ultrasonic transducers are designed using Aluminum nitride (AlN) piezoelectric thin film as the piezoelectric element and using silicon lens for focusing. The fabrication and characterization of silicon lens was presented in detail. Finite element simulation was used for transducer design and evaluation. A custom designed LNA circuit is presented for amplifying the ultrasound echo signal with low noise. A Common-source and Common-gate (CS-CG) combination structure with active feedback is adopted for the LNA design so that high gain and wideband performances can be achieved simultaneously. Noise and distortion cancelation mechanisms are also employed in this work to improve the noise figure (

Indexed as

finite element simulationlow noise amplifier (LNA)noise figureSi lenstight focusultrahigh frequency ultrasonic transducer

Identifiers

PMID30424448
PMCPMC6215185

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.