Evidence map›Paper›PMID 36837969›Full record

ArticleMicromachines2023

A Novel Miniature and Selective CMOS Gas Sensor for Gas Mixture Analysis-Part 3: Extending the Chemical Modeling.

Boris Goikhman, Moshe Avraham, Sharon Bar-Lev, Sara Stolyarova, Tanya Blank, Yael Nemirovsky

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 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. 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.

Boris GoikhmanElectrical and Computer Engineering Department, Technion-Israel Institute of Technology, Haifa 32000, Israel.
Moshe AvrahamElectrical and Computer Engineering Department, Technion-Israel Institute of Technology, Haifa 32000, Israel.
Sharon Bar-LevElectrical and Computer Engineering Department, Technion-Israel Institute of Technology, Haifa 32000, Israel.
Sara StolyarovaElectrical and Computer Engineering Department, Technion-Israel Institute of Technology, Haifa 32000, Israel.
Tanya BlankElectrical and Computer Engineering Department, Technion-Israel Institute of Technology, Haifa 32000, Israel.
Yael NemirovskyElectrical and Computer Engineering Department, Technion-Israel Institute of Technology, Haifa 32000, Israel.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This is the third part of the paper presenting a miniature, combustion-type gas sensor (dubbed GMOS) based on a novel thermal sensor (dubbed TMOS). The TMOS is a micromachined CMOS-SOI transistor, which acts as the sensing element and is integrated with a catalytic reaction plate, where ignition of the gas takes place. The first part was focused on the chemical and technological aspects of the sensor. In Part 2, the emphasis was on the physical aspects of the reaction micro-hot plate on which the catalytic layer is deposited. The present study focuses on applying several advanced simulation tools, which extend our understanding of the GMOS performance, as well as pellistor sensors in general. The three main challenges in simulating the performance are: (i) how to define the operating temperature based on the input parameters; (ii) how to measure the dynamics of the temperature increase during cyclic operation at a given duty cycle; (iii) how to model the correlation between the operating temperature and the sensing response. The simulated and analytical models and measured results are shown to be in good agreement.

Indexed as

CFDgas sensorGMOSpellistorTMOS

Identifiers

PMID36837969
PMCPMC9963620

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.