Ferromagnetic Ni_1-VO_1- Nano-Clusters for NO Detection at Room Temperature: A Case of Magnetic Field-Induced...

Surface modulation of functional nanostructures is an efficient way of improving gas sensing properties in chemiresistive materials. However, synthesis methods employed so far in achieving desired performances are cumbersome and energy intensive. Moreover, nano-engineering-induced magnetic properties of these materials which are expected to enhance sensing responses have not been utilized until now in improving their interaction with target gases. In particular for gasses with paramagnetic nature such as NO or NO₂, the inherent magnetic property of the chemiresistor might assist in enabling superior sensing performance. In this work, vanadium-doped NiO nano-clusters with ferromagnetic behavior at room temperature have been synthesized by a simple and effective combination of soft chemical routes and employed in efficient and selective detection of paramagnetic NO gas. While NiO is typically anti-ferromagnetic, the nanoscale engineering of NiO- and V-doped NiO samples have been found to tune the inherent anti-ferromagnetic behavior into room-temperature ferromagnetism. Surface modification in terms of formation of nano-clusters led to an increased Brunauer-Emmett-Teller surface area of ∼120 m²/g. The sample Ni_0.636V_0.364O has been observed to exhibit a selective and high response of ∼98% to 1 ppm NO at room temperature with fast response (14 s) and recovery (95 s). The improved sensing response of this sample compared to other doped NiO variants could be explained in terms of lower remnant magnetic moment of the sample accompanied with higher excess negative charge at the surface. The sensing response of this sample was increased by 30% in the presence of an external magnetic field of 280 gauss, highlighting the importance of magnetic ordering in chemiresistive gas sensing between the magnetic sensor material and target analyte. This material stands as a potential gas sensor with excellent NO detection properties.