Comprehensive analysis of reaction mechanisms in reduced graphene oxide and hematite heterostructure gas sensors

被引:14
作者
Ahmad, Ibtisam [1 ]
Lee, Doowon [1 ]
Mehmood, Shahid [2 ]
Chae, Myoungsu [1 ]
Ali, Awais [3 ]
Aftab, Jamshed [3 ]
Bhatti, Arshad Saleem [2 ,3 ]
Karamat, Shumaila [4 ]
Kim, Hee-Dong [1 ]
机构
[1] Sejong Univ, Inst Semicond & Syst IC, Dept Semicond Syst Engn & Convergence Engn Intelli, 209 Neungdong Ro, Seoul 05006, South Korea
[2] Virtual Univ Pakistan, Def Rd,Off Raiwind Rd, Lahore 54660, Pakistan
[3] COMSATS Univ Islamabad, Ctr Micro & Nano Devices, Dept Phys, Islamabad 44000, Pakistan
[4] COMSATS Univ Islamabad, Dept Phys, Islamabad 44000, Pakistan
基金
新加坡国家研究基金会;
关键词
rGO-Fe; 2; O; 3; heterostructure; Gas sensor; Formaldehyde detection; SENSING PROPERTIES; FORMALDEHYDE; TEMPERATURE; NANOSTRUCTURES; PARTICLES; ACETONE; FILM;
D O I
10.1016/j.jallcom.2023.171698
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
Exposure to formaldehyde (HCHO) in humans causes various types of diseases, such as asthma, lung cancer, and nasal cancer depending on the exposure, which leads to death in severe cases. Many types of gas sensors are being studied in order to sense HCHO, but the sensors cannot detect below the WHO standard of 0.08 ppm. We present a highly sensitive and inexpensive HCHO gas sensor with a heterostructure of reduced graphene oxide (rGO) and hematite (Fe2O3) in this study. In addition, rGO and Fe2O3-based gas sensors are prepared in order to compare the response characteristics with the proposed heterostructure-based gas sensor. As a result, we observed a high response of 309 % for an HCHO of 100-ppm, which is 10 times higher compared to the reference sensors. We also addressed a neural network analysis to predict the response characteristics of the unmeasured HCHO concentration, and we obtained the highest accuracy, which was above 90 %, when we used the sigmoid model-based neural network model. These results facilitate the realization of ultra-sensitive gas sensors to HCHO gas, which lead to prevent various types of diseases.
引用
收藏
页数:12
相关论文
共 35 条
[1]  
PBAG, 2015, Journal of Nanomedicine & Nanotechnology, V06, DOI [10.4172/2157-7439.1000253, 10.4172/2157-7439.1000253, DOI 10.4172/2157-7439.1000253]
[2]  
Boukhoubza I., 2019, Journal of Physics: Conference Series, V1292, DOI [10.1088/1742-6596/1292/1/012011, 10.1088/1742-6596/1292/1/012011]
[3]   Size-dependent structural transformations of hematite nanoparticles. 1. Phase transition [J].
Chernyshova, I. V. ;
Hochella, M. F., Jr. ;
Madden, A. S. .
PHYSICAL CHEMISTRY CHEMICAL PHYSICS, 2007, 9 (14) :1736-1750
[4]   Adsorption of formaldehyde molecule on the intrinsic and Al-doped graphene: A first principle study [J].
Chi, Mei ;
Zhao, Ya-Pu .
COMPUTATIONAL MATERIALS SCIENCE, 2009, 46 (04) :1085-1090
[5]   Facile synthesis of pseudo-peanut shaped hematite iron oxide nano-particles and their promising ethanol and formaldehyde sensing characteristics [J].
Das, P. ;
Mondal, B. ;
Mukherjee, K. .
RSC ADVANCES, 2014, 4 (60) :31879-31886
[6]   Monodisperse hematite porous nanospheres: synthesis, characterization, and applications for gas sensors [J].
Gou, Xinglong ;
Wang, Guoxiu ;
Park, Jinsoo ;
Liu, Hao ;
Yang, Juan .
NANOTECHNOLOGY, 2008, 19 (12)
[7]   Nitrogen-Doped Graphene as Electrode Material with Enhanced Energy Density for Next-Generation Supercapacitor Application [J].
Kesavan, T. ;
Aswathy, R. ;
Raj, I. Arul ;
Kumar, T. Prem ;
Ragupathy, P. .
ECS JOURNAL OF SOLID STATE SCIENCE AND TECHNOLOGY, 2015, 4 (12) :M88-M92
[8]   Zinc Oxide Nanostructures for NO2 Gas-Sensor Applications: A Review [J].
Kumar, Rajesh ;
Al-Dossary, O. ;
Kumar, Girish ;
Umar, Ahmad .
NANO-MICRO LETTERS, 2015, 7 (02) :97-120
[9]   A self-heating gas sensor with integrated NiO thin-film for formaldehyde detection [J].
Lee, Chia-Yen ;
Chiang, Che-Ming ;
Wang, Yu-Hsiang ;
Ma, Rong-Hua .
SENSORS AND ACTUATORS B-CHEMICAL, 2007, 122 (02) :503-510
[10]   Reduced graphene oxide/MoS2 hybrid films for room-temperature formaldehyde detection [J].
Li, Xian ;
Wang, Jing ;
Xie, Dan ;
Xu, Jianlong ;
Xia, Yi ;
Xiang, Lan ;
Komarneni, Sridhar .
MATERIALS LETTERS, 2017, 189 :42-45