2017年
電池駆動MEMS天然ガスセンサーの開発
日本エネルギー学会機関誌えねるみくす
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発表資料
回数 : 0
- ,
- 巻
- 96
- 号
- 4
- 開始ページ
- 422
- 終了ページ
- 426
- 記述言語
- 日本語
- 掲載種別
- DOI
- 10.20550/jieenermix.96.4_422
- 出版者・発行元
- 一般社団法人 日本エネルギー学会
<p>A natural gas sensor that detects methane, the main component of natural gas, plays a very important role in securing safety and security in exploration, production, transportation, supply and consumption stage of natural gas. However, AC power supply was necessary to install equipment such as leak detectors and gas leak alarms, because power consumption for heating sensor is too much. In order to realize battery-driven equipment, power consumption of a sensor must be suppressed to several hundredths of the conventional sensors. We have developed a MEMS(Micro Electro Mechanical Systems)methane sensor based on a catalytic thick film/SnO2 thin film bilayer. Ultra-low power consumption was achieved by microminiaturizing, and driving with low power ultra-short pulse. Furthermore, this sensor has realized higher sensitivity and higher selectivity than conventional methane sensors. In May 2015, Osaka Gas released the world's first battery-driven city gas leak alarm equipped with this sensor. This technology can greatly contribute to suppression of gas leakage accidents, because it is possible to realize easier and less expensive installation of natural gas leak detector or gas leak alarm at a place where it took a great deal of time and expense for laying or relocating power supply.</p>
- リンク情報
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- DOI
- https://doi.org/10.20550/jieenermix.96.4_422
- J-GLOBAL
- https://jglobal.jst.go.jp/detail?JGLOBAL_ID=201702241343262622
- CiNii Books
- http://ci.nii.ac.jp/ncid/AA12772593
- CiNii Research
- https://cir.nii.ac.jp/crid/1390282681110468096?lang=ja
- URL
- https://www.jstage.jst.go.jp/article/jieenermix/96/4/96_422/_pdf/-char/ja
- URL
- http://id.ndl.go.jp/bib/028398887
- ID情報
-
- DOI : 10.20550/jieenermix.96.4_422
- ISSN : 2432-3586
- eISSN : 2432-3594
- J-Global ID : 201702241343262622
- CiNii Articles ID : 130006590708
- CiNii Books ID : AA12772593
- CiNii Research ID : 1390282681110468096