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Potentiometric-Type Gas Sensor Using MgFe2O4 Sensing Electrode for Detection of Hydrocarbon Based on Carbon Number.
Anggraini, Sri Ayu; Fujio, Yuki; Ikeda, Hiroshi.
Afiliação
  • Anggraini SA; Sensing System Research Center (SSRC), National Institute of Advanced Industrial Science and Technology (AIST), Tosu, Saga 841-0052, Japan.
  • Fujio Y; Sensing System Research Center (SSRC), National Institute of Advanced Industrial Science and Technology (AIST), Tosu, Saga 841-0052, Japan.
  • Ikeda H; Division of Biomaterials, Department of Oral Functions, Kyushu Dental University, Kita Kyushu, Fukuoka 803-8580, Japan.
ACS Sens ; 8(7): 2514-2518, 2023 07 28.
Article em En | MEDLINE | ID: mdl-37433097
Hydrocarbon (HC) monitoring is necessary for safe and effective operations in industries such as petroleum and gas. In this study, total hydrocarbons can be detected by using yttria-stabilized zirconia (YSZ)-based potentiometric-type gas sensor using MgFe2O4 sensing electrode (SE). The sensor was found to generate a similar response magnitude to those of hydrocarbons that have the same carbon number, irrespective of the type of carbon bond (total hydrocarbon detection). Aside from being capable of detecting total hydrocarbons sensitively and selectively with rapid response time, the sensor using MgFe2O4-SE also exhibited a linear relationship between sensor responses and carbon number. In addition to that, the developed sensor showed a logarithmically linear relationship between sensor responses and HC concentration in the range 20-700 ppm. These sensing characteristics were confirmed to be reproducible, and sensor responses toward HC were found to be repeatable and gradually decreased with increasing in O2 concentration in the range of 3-21 vol %.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Carbono / Hidrocarbonetos Tipo de estudo: Diagnostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Carbono / Hidrocarbonetos Tipo de estudo: Diagnostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article