EventsMOL2NET'19, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 5th ed.
Published
This submission belongs to the session 06. NANOMATJND-05: JSU-NDSU Nanotech. & Materials Science Workshop, Jackson & Fargo, USA, 2019 of the event MOL2NET'19, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 5th ed.
Published date
02 Dec, 2019
Citation
Srinivasulu Kanaparthi, Shiv Govind Singh, Ultra-sensitive detection of H₂S with 2D ZnO nanostructures, in Proceedings of MOL2NET'19, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 5th ed., 20 March–20 December 2019, MDPI: Basel, Switzerland, doi: 10.3390/mol2net-05-06722
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Ultra-sensitive detection of H2S with 2D ZnO nanostructures

Shiv Govind Singh 1
1. Department of Electrical Engineering, Indian Institute of Technology Hyderabad, India
Abstract

The toxic gases released by industries and other sources have a significant impact on humans and other life on the earth. Exposure to these gases at higher concentration may cause severe health issues and may even lead to death. Thus, the rapid detection of hazardous gases in the environment with high sensitivity is crucial to save the lives. However, the low sensitivity of the existing sensors limits their usage in detecting toxic gases in the air. To address this, we report a highly sensitive Hydrogen Sulfide (H2S) gas sensor based on 2D Zinc Oxide (ZnO) nanostructures. H2S is a poisonous and flammable gas and as per American Conference of Government Industrial Hygienists, the acceptable limit of H2S in the air is 10 ppm. When the concentration exceeds 10 ppm, the human nose loses the ability to detect H2S, which causes disastrous effects. The proposed sensor was tested in the range of 0.5-4 ppm H2S and it exhibited a response of 750% upon exposure of 4 ppm H2S. The response and recovery times are < 250 seconds and <430 seconds respectively in the tested range of concentrations of target gas.

Keywords
gas sensor
Hyderogen Sulfide sensor
ZnO nanostructures
Manuscript
Rapid detection of target gases with an early prediction approach
Effect of nanoparticles and nanomaterials as biostimulants