Highly sensitive prismatic h-MoO3 sheets for temperature-dependent chemiresistive ammonia sensor.

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Title: Highly sensitive prismatic h-MoO3 sheets for temperature-dependent chemiresistive ammonia sensor.
Authors: Muthumalai, K.1 (AUTHOR), Panjulingam, Nandhini2 (AUTHOR), Manoharan, Mathankumar1 (AUTHOR), Govindharaj, Kamaraj1 (AUTHOR), Saravanan, Poovarasan1 (AUTHOR), Lakshmipathi, Senthilkumar2 (AUTHOR), Haldorai, Yuvaraj3 (AUTHOR), Rajendra Kumar, Ramasamy Thangavelu1 (AUTHOR) rtrkumar@buc.edu.in
Source: Journal of Materials Science: Materials in Electronics. Apr2024, Vol. 35 Issue 10, p1-13. 13p.
Abstract: Molybdenum trioxide (MoO3) is an excellent material for chemiresistive gas sensors. In this report, we investigated the ammonia sensing behavior of hexagonal (h-MoO3) and orthorhombic (α-MoO3) MoO3. X-ray diffraction study verified the existence of two distinct phases of MoO3. Scanning electron microscopic images revealed that the hydrothermally synthesized h-MoO3 showed prismatic sheets while the α-MoO3 prepared by reflux condensation exhibited agglomerated micropellets. The presence of oxygen vacancies in h-MoO3 was confirmed by high-resolution transition electron microscopy and X-ray photoelectron spectroscopy. The as-fabricated h-MoO3 chemiresistive sensor showed an eight-fold higher sensing response than α-MoO3 for ammonia. The calculated limit of detection was 0.47 ppm, and the sensor exhibited good stability for 60 days. The density functional theory simulation suggested that the relatively higher adsorption energy and charge transfer could be the reason for its higher sensitivity when compared to α-MoO3. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Materials Science: Materials in Electronics is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Highly sensitive prismatic h-MoO<subscript>3</subscript> sheets for temperature-dependent chemiresistive ammonia sensor.
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Materials+Science%3A+Materials+in+Electronics%22">Journal of Materials Science: Materials in Electronics</searchLink>. Apr2024, Vol. 35 Issue 10, p1-13. 13p.
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Molybdenum trioxide (MoO3) is an excellent material for chemiresistive gas sensors. In this report, we investigated the ammonia sensing behavior of hexagonal (h-MoO3) and orthorhombic (α-MoO3) MoO3. X-ray diffraction study verified the existence of two distinct phases of MoO3. Scanning electron microscopic images revealed that the hydrothermally synthesized h-MoO3 showed prismatic sheets while the α-MoO3 prepared by reflux condensation exhibited agglomerated micropellets. The presence of oxygen vacancies in h-MoO3 was confirmed by high-resolution transition electron microscopy and X-ray photoelectron spectroscopy. The as-fabricated h-MoO3 chemiresistive sensor showed an eight-fold higher sensing response than α-MoO3 for ammonia. The calculated limit of detection was 0.47 ppm, and the sensor exhibited good stability for 60 days. The density functional theory simulation suggested that the relatively higher adsorption energy and charge transfer could be the reason for its higher sensitivity when compared to α-MoO3. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
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  Data: <i>Copyright of Journal of Materials Science: Materials in Electronics is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1007/s10854-024-12468-w
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              Text: Apr2024
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