Evidence map›Paper›PMID 30986913›Full record

ArticleSensors (Basel, Switzerland)2019

Dynamic pH Sensor with Embedded Calibration Scheme by Advanced CMOS FinFET Technology.

Chien-Ping Wang, Ying-Chun Shen, Peng-Chun Liou, Yu-Lun Chueh, Yue-Der Chih, Jonathan Chang, Chrong-Jung Lin, Ya-Chin King

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Chien-Ping WangInstitute of Electronics Engineering, National Tsing Hua University, Hsinchu 30013, Taiwan. jpwang.starlab@gmail.com.
Ying-Chun ShenInstitute of Materials Science and Engineering, National Tsing Hua University, Hsinchu 30013, Taiwan. kuroekyo@gmail.com.
Peng-Chun LiouInstitute of Electronics Engineering, National Tsing Hua University, Hsinchu 30013, Taiwan. pjliou.starlab@gmail.com.
Yu-Lun ChuehInstitute of Materials Science and Engineering, National Tsing Hua University, Hsinchu 30013, Taiwan. ylchueh@mx.nthu.edu.tw.
Yue-Der ChihDesign Technology Division, Taiwan Semiconductor Manufacturing Company, Hsinchu 30075, Taiwan. ydchih@tsmc.com.
Jonathan ChangDesign Technology Division, Taiwan Semiconductor Manufacturing Company, Hsinchu 30075, Taiwan. jon_chang@tsmc.com.
Chrong-Jung LinInstitute of Electronics Engineering, National Tsing Hua University, Hsinchu 30013, Taiwan. cjlin@ee.nthu.edu.tw.
Ya-Chin KingInstitute of Electronics Engineering, National Tsing Hua University, Hsinchu 30013, Taiwan. ycking@ee.nthu.edu.tw.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this work, we present a novel pH sensor using efficient laterally coupled structure enabled by Complementary Metal-Oxide Semiconductor (CMOS) Fin Field-Effect Transistor (FinFET) processes. This new sensor features adjustable sensitivity, wide sensing range, multi-pad sensing capability and compatibility to advanced CMOS technologies. With a self-balanced readout scheme and proposed corresponding circuit, the proposed sensor is found to be easily embedded into integrated circuits (ICs) and expanded into sensors array. To ensure the robustness of this new device, the transient response and noise analysis are performed. In addition, an embedded calibration operation scheme is implemented to prevent the proposed sensing device from the background offset from process variation, providing reliable and stable sensing results.

Indexed as

calibration operationCMOS FinFET technologypH sensorsreadout circuit scheme

Identifiers

PMID30986913
PMCPMC6480048

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Registered trials

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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.