Materials Engineering Strategies to Control Metal Oxides Nanowires Sensing Properties

Navpreet Kaur, Mandeep Singh, Elisabetta Comini
2021 Advanced Materials Interfaces  
such as transistors, solar cells, batteries, superconductivity, and so on. In particular, nanostructured MOXs were found to be highly efficient as active layers of sensors due to their high surfaceto-volume ratio, high crystallinity, and excellent stoichiometry. Over the years, many MOXs such as zinc oxide (ZnO), nickel oxide (NiO), tin oxide (SnO 2 ), etc. were synthesized in different nanostructured forms (nanotubes, nanorods, nanobelts, etc.) and successfully explored as an active sensing
more » ... er for the detection of various gas analytes. However, in the last few years, MOXs in nanowires (NWs) morphology were gaining great attention due to their well-defined crystal orientation, single crystallinity, excellent electrical properties, and faster response dynamics as gas diffusion prior to surface reactions is not required. [1] esides their success, MOXs nanowires still suffer from selectivity and high temperature operation issues. To further improve their performances and overcome these obstacles, nowadays researchers are working on the modification of nanowires via different strategies. These strategies include nanowires heterostructures, quasi-1D core-shell structures, particle decoration, surface functionalization with self-assembled monolayers (SAMs), modification with graphene and MOX@MOF coresheath structures. Nanowires based heterostructures may synergistically combine the properties of two different materials in a single sensing platform at nanoscale level. [2] While, coreshell structures offer high surface area, lower rate of charge recombination, and full depletion regions, which are desirable properties to increase the sensing performance. [3] Moreover, nanowires functionalized with SAM molecules enhance the surface-specific interaction with gas analytes due to the presence of SAM functional groups; hence, improves the sensor selectivity. [4, 5] n this review article, the above-mentioned strategies to improve the sensing performance of MOXs nanowires based chemoresistive sensors have been reviewed. In particular, attention has been paid to summarize the gas sensing mechanism suggested by the authors along with improvement in the sensor response, detection limits and working temperatures. The last decade's works have been reviewed in this review article. Moreover, the working principle of conductometric gas sensors, gas sensing mechanism, and synthesis techniques were briefly discussed. Metal oxides (MOXs), in the form of nanowires, have proved to be an excellent active sensing layer of chemoresistive sensors due to their unique physical/chemical properties such as single crystallinity, exceptional electrical properties, and so on. Indeed, MOXs nanowires-based gas sensors show fast dynamic response with excellent reproducibility, stability, and reactivity toward various gas analytes. However, their limited selectivity and high operation temperature that lead to high power consumption are still major issues that need to be addressed. To improve these characteristics, researchers nowadays are working in the direction of modifying nanowires with different strategies. These strategies include nanowires heterostructures, decoration with particles (metals and metal oxides), core-shell structures, and surface functionalization with self-assembled monolayers and modification with graphene (pristine and oxidized). By employing these strategies, nanowires sensing performances, especially their selectivity, sensitivity, and response, can immensely enhance. Hence, in this review article, the above-mentioned strategies to improve the sensing performance of MOXs nanowires are reviewed. Attention is paid to underlying sensing mechanisms and improved sensing characteristics. In addition, MOXs gas sensing mechanism, working principle of conductometric gas sensors, and different synthesis techniques, used to modify nanowires, are also briefly discussed.
doi:10.1002/admi.202101629 fatcat:r4kgplxmh5d4tlcwdl5pc3ua4e