Facile engineering of metal-organic framework derived SnO2@NiO core-shell nanocomposites based gas sensor toward superior VOCs sensing performance

Aiming to achieve high-sensitivity volatile organic compounds (VOCs), it is of great significance to continuously enhance the sensing performance of metal oxide based sensors. Herein, novel NiO nanoplates-decorated on SnO2 nanofibers 1D core-shell structures derived from metal-organic frameworks (MOFs) are fabricated by the facial solvothermal method and heat treatment for VOCs gas sensors. The morphology and composition of 1D core shell SnO2@NiO are regulated by solvothermal time in the range of 0 similar to 24 h. Based on the unique structure and composition of SnO2@NiO, SnO2@NiO with 4 h solvothermal time (denoted as SnO2@NiO-4) exhibits excellent selectivity, high response (R-a/R-g = 25.6) and low detection limit as well as good response linearity between response and concentration of xylene. Especially, the obtained SnO2@NiO-8 and SnO2@NiO-16 show the high sensitivity to acetone (R-a/R-g = 28.7) and triethylamine (R-a/R-g = 13.7), respectively. Structural characterizations such as SEM, TEM, and Mott-Schottky results demonstrate the core-shell structure with p-n heterojunction. In-depth investigations on reaction mechanism reveal XPS, photoluminescence (PL), and ESR testing reveal the intrinsic defects such of oxygen vacancy and Ni3+ active sites. And in situ FTIR, online mass spectroscopy, as well as UV/UPS analysis further discover the evolution of intermediates and products during the surface catalysis reaction. These results demonstrate that the remarkable sensing performance of SnO2@NiO-8 can be attributed to several factors, including abundant oxygen vacancy, formation of p-n heterostructure and efficient Ni3+/Ni2+ catalyzing, which beneficial for increased active sites and enhanced electron transport. This synthetic strategy provides an effective method for the facile engineering of high-performances metal oxide-based sensors towards practical health assessment.