Abstract
An array comprised of four magnonic gas sensors based on magnetic nanoparticles layers of CuFe2O4, MnFe2O4, ZnFe2O4 and CoFe2O4 was developed and tested with dymethylformamide, isopropanol, xylene and toluene. Magnonic gas sensors were composed of an yttrium iron garnet (YIG) epitaxial thin film as a magnetostatic spin waveguide combined with a spin-coated layer of magnetic nanoparticles as a sensitive layer. The magnetostatic spin waves (MSW) were very sensitive to perturbations produced in the magnetic properties of the nanoparticle layers due to interaction with gases, allowing the detection of low concentrations of gases. Finally, the sensitive layers of the magnetic nanoparticles revealed a differentiated response in regard to the gases used to test the array. Therefore, the gases could be discriminated and classified using pattern recognition techniques, such as principal component analysis and artificial neural networks.
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