Green and low-cost synthesis of zinc oxide nanoparticles and their application in transistor-based carbon monoxide sensing

RSC ADVANCES(2020)

引用 64|浏览3
暂无评分
摘要
There has been steady progress in developing reliable and cost-effective strategies for the clean production of zinc oxide (ZnO) nanoparticles (NPs) owing to their unique structural and wide functional characteristics. While the green synthesis of such NPs from plant extracts has emerged as a sustainable and eco-friendly protocol, it is greatly restricted owing to the scarcity of potential natural precursors necessitating comprehensive investigations in this direction. Herein, we report a facile, low-cost green synthesis and characterization of ZnO NPs along with the demonstration of their usage as an active media in organic field-effect transistor (OFET) devices for sensing carbon monoxide (CO) gas. The ZnO NPs obtained from Nelumbo nucifera (lotus) leaf extract-mediated solution combustion synthesis at a much lower initiation temperature, the first of its kind, were characterized by various techniques such as UV-vis spectroscopy, XRD, EDX analysis, TEM and FESEM. The data derived from these experiments clearly evidence the formation of very pure and crystalline ZnO NPs possessing nearly spherical-shape with a size of 3-4 nm. The p-type organic field-effect transistor (OFET) device, fabricated using poly(3-hexylthiophene-2,5-diyl) (P3HT) and ZnO NPs, showed a field-effect mobility of 10(-2) cm(2) V-1 sec(-1) with a slightly enhanced response of detecting CO gas at room temperature (RT). The phenomenon was further confirmed by the variation in electrical parameters of the OFET such as field-effect mobility (mu), on-current (I-on), and off-current (I-off). The selectivity and sensitivity of the fabricated device in CO gas detection was found to be more prominent than the other reducing gases (hydrogen sulphide, H2S and ammonia, NH3) and methanol vapours tested.
更多
查看译文
关键词
zinc oxide nanoparticles,carbon monoxide sensing,carbon monoxide,low-cost,transistor-based
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要