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Li G, Su Y, Chen XX, Chen L, Li YY, Guo Z. Enhanced chemiresistive sensing performance of well-defined porous CuO-doped ZnO nanobelts toward VOCs. NANOSCALE ADVANCES 2019; 1:3900-3908. [PMID: 36132089 PMCID: PMC9419800 DOI: 10.1039/c9na00163h] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/15/2019] [Accepted: 08/10/2019] [Indexed: 06/01/2023]
Abstract
Although the post-doping approach as a typical and effective method has been widely employed to improve the gas sensing performance of nanostructured metal oxides, it easily breaks their porous nanostructures. Herein a facile partial cation-exchange strategy combined with thermal oxidation has been developed to prepare porous CuO-doped ZnO nanobelts. Using ZnSe·0.5N2H4 nanobelts as the precursor template, Cu2Se-doped precursor nanobelts were obtained with Zn2+ cations partially exchanged by Cu2+ cations. After annealing in air, they are further oxidized into well-defined porous CuO-doped ZnO nanobelts. Through manipulating the amount of exchanged Cu2+ cations, the CuO-doping concentration can be precisely tuned. Based on the assembly approach and in situ thermal oxidation, a uniform and stable sensing film consisting of porous CuO-doped nanobelts was fabricated. Compared with pristine porous ZnO nanobelts, the as-prepared porous CuO-doped nanobelts with p-type CuO|n-type ZnO heterojunctions exhibited better sensing performance toward volatile organic compounds (VOCs). Especially for 3 at% CuO-doped porous ZnO nanobelts, the relative responses toward 100 ppm of ethanol, acetone and formaldehyde were greatly enhanced more than two, four and ten times, respectively. Due to the porous structure, they also displayed a fast response/recovery time. Finally, this enhanced sensing mechanism was discussed for porous CuO-doped ZnO nanobelts.
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Affiliation(s)
- Gang Li
- Institutes of Physical Science and Information Technology, Anhui University Hefei 230601 People's Republic of China
- Key Laboratory of Environmental Optics and Technology, Institute of Intelligent Machines, Chinese Academy of Sciences Hefei 230031 People's Republic of China
| | - Yao Su
- Key Laboratory of Environmental Optics and Technology, Institute of Intelligent Machines, Chinese Academy of Sciences Hefei 230031 People's Republic of China
| | - Xu-Xiu Chen
- Institutes of Physical Science and Information Technology, Anhui University Hefei 230601 People's Republic of China
| | - Li Chen
- Institutes of Physical Science and Information Technology, Anhui University Hefei 230601 People's Republic of China
| | - Yong-Yu Li
- Institutes of Physical Science and Information Technology, Anhui University Hefei 230601 People's Republic of China
- Key Laboratory of Environmental Optics and Technology, Institute of Intelligent Machines, Chinese Academy of Sciences Hefei 230031 People's Republic of China
| | - Zheng Guo
- Institutes of Physical Science and Information Technology, Anhui University Hefei 230601 People's Republic of China
- Key Laboratory of Environmental Optics and Technology, Institute of Intelligent Machines, Chinese Academy of Sciences Hefei 230031 People's Republic of China
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Li YX, Guo Z, Su Y, Jin XB, Tang XH, Huang JR, Huang XJ, Li MQ, Liu JH. Hierarchical Morphology-Dependent Gas-Sensing Performances of Three-Dimensional SnO 2 Nanostructures. ACS Sens 2017; 2:102-110. [PMID: 28722446 DOI: 10.1021/acssensors.6b00597] [Citation(s) in RCA: 53] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Hierarchical morphology-dependent gas-sensing performances have been demonstrated for three-dimensional SnO2 nanostructures. First, hierarchical SnO2 nanostructures assembled with ultrathin shuttle-shaped nanosheets have been synthesized via a facile and one-step hydrothermal approach. Due to thermal instability of hierarchical nanosheets, they are gradually shrunk into cone-shaped nanostructures and finally deduced into rod-shaped ones under a thermal treatment. Given the intrinsic advantages of three-dimensional hierarchical nanostructures, their gas-sensing properties have been further explored. The results indicate that their sensing behaviors are greatly related with their hierarchical morphologies. Among the achieved hierarchical morphologies, three-dimensional cone-shaped hierarchical SnO2 nanostructures display the highest relative response up to about 175 toward 100 ppm of acetone as an example. Furthermore, they also exhibit good sensing responses toward other typical volatile organic compounds (VOCs). Microstructured analyses suggest that these results are mainly ascribed to the formation of more active surface defects and mismatches for the cone-shaped hierarchical nanostructures during the process of thermal recrystallization. Promisingly, this surface-engineering strategy can be extended to prepare other three-dimensional metal oxide hierarchical nanostructures with good gas-sensing performances.
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Affiliation(s)
- Yi-Xiang Li
- Nanomaterials
and Environmental Detection Laboratory, Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei 230031, PR China
- Department
of Chemistry, University of Science and Technology of China, Hefei 230026, PR China
| | - Zheng Guo
- Nanomaterials
and Environmental Detection Laboratory, Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei 230031, PR China
- Department
of Chemistry, University of Science and Technology of China, Hefei 230026, PR China
| | - Yao Su
- Nanomaterials
and Environmental Detection Laboratory, Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei 230031, PR China
- Department
of Chemistry, University of Science and Technology of China, Hefei 230026, PR China
| | - Xiao-Bo Jin
- Nanomaterials
and Environmental Detection Laboratory, Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei 230031, PR China
| | - Xiang-Hu Tang
- Nanomaterials
and Environmental Detection Laboratory, Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei 230031, PR China
| | - Jia-Rui Huang
- Department
of Chemistry, Anhui Normal University, Wuhu 241000, PR China
| | - Xing-Jiu Huang
- Nanomaterials
and Environmental Detection Laboratory, Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei 230031, PR China
- Department
of Chemistry, University of Science and Technology of China, Hefei 230026, PR China
| | - Min-Qiang Li
- Nanomaterials
and Environmental Detection Laboratory, Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei 230031, PR China
- Department
of Chemistry, University of Science and Technology of China, Hefei 230026, PR China
| | - Jin-Huai Liu
- Nanomaterials
and Environmental Detection Laboratory, Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei 230031, PR China
- Department
of Chemistry, University of Science and Technology of China, Hefei 230026, PR China
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