Journal
ACS APPLIED MATERIALS & INTERFACES
Volume 13, Issue 12, Pages 14460-14470Publisher
AMER CHEMICAL SOC
DOI: 10.1021/acsami.0c20566
Keywords
gas-sensing composite materials; vapor-induced self-assembly; metal halide perovskite; heterojunction; machine learning method; breath detection materials
Funding
- Joint Project of Industry-University-Research of Jiangsu Province [2016h036, 2018h020]
- Jiangsu Provincial Government Scholarship [20199622]
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By adjusting the heterostructure between CsPbI3 nanocrystals and SMO nanomaterials, the sensitivity of SMOs can be enhanced. The CsPbI3NC-SnO(2)QNP/MWCNT nanocomposite exhibited superior stability and sensing response, with excellent selectivity towards NH3. This work provides insight into the rational design of metal halide perovskite/SMO heterojunctions for high-performance sensing applications.
It is an effective strategy to enhance the sensitivity of semiconductor metal oxides (SMOs) being sensitized with CsPbI3 nanocrystals (NCs) by adjusting the heterostructure between CsPbI3NC and SMO nanomaterials. In this work, for the first time, a porous 3D multiple-walled carbon nanotube (MWCNT) network uniformly coated with SnO2 quantum nanoparticles (QNPs) and CsPbI3 nanocrystals were prepared via a simple solvent vapor-induced self-assembly method. The fabricated CsPbI3NC-SnO(2)QNP/MWCNT nanocomposite with vapor-induced self-assembly exhibits superior stability against the moisture as well as an excellent sensing response. The results imply that the rational design of the metal halide perovskite NC/SMO heterostructure can not only improve the stability but also meet the requirements of sensing application. The self-assembled SnO(2)QNP/MWCNT can facilitate the dispersion of small-sized nanoparticles and efficaciously prevent the detachment of CsPbI3NC. Compared with pristine SnO(2)QNP and SnO2/MWCNT sensors, the CsPbI3NC-modified SnO(2)QNP/MWCNT nanostructure exhibited a remarkable sensitivity of 39.2 for 0.2 ppm NH3, rapid response/recovery time of 17/18 s, and excellent selectivity towards NH3. In particular, we applied machine learning methods, including principal component analysis (PCA) and support vector machines (SVMs), to analyze the sensing performance of the CsPbI3NC-SnO(2)QNP/MWCNT sensor and found that the combined effects of CsPbI3NC-SnO(2)QNP/MWCNT heterointerfaces contributed to the improvement of selectivity of sensors. The excellent NH3 for sub-ppm level concentration is ascribed to the high sensing activity of the CsPbI3 NC-based heterojunction. This work may not only enrich the family of high-performance breath detection materials but also provide a good example for designing reasonable composite materials with specific properties in the field of metal halide perovskite/SMO heterojunctions.
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