A magnonic gas sensor based on magnetic nanoparticles.

In this paper, we propose an innovative, simple and inexpensive gas sensor based on the variation in the magnetic properties of nanoparticles due to their interaction with gases. To measure the nanoparticle response a magnetostatic spin wave (MSW) tunable oscillator has been developed using an yttrium iron garnet (YIG) epitaxial thin film as a delay line (DL). The sensor has been prepared by coating a uniform layer of CuFe2O4 nanoparticles on the YIG film. The unperturbed frequency of the oscillator is determined by a bias magnetic field, which is applied parallel to the YIG film and perpendicularly to the wave propagation direction. In this device, the total bias magnetic field is the superposition of the field of a permanent magnet and the field associated with the layer of magnetic nanoparticles. The perturbation produced in the magnetic properties of the nanoparticle layer due to its interaction with gases induces a frequency shift in the oscillator, allowing the detection of low concentrations of gases. In order to demonstrate the ability of the sensor to detect gases, it has been tested with organic volatile compounds (VOCs) which have harmful effects on human health, such as dimethylformamide, isopropanol and ethanol, or the aromatic hydrocarbons like benzene, toluene and xylene more commonly known by its abbreviation (BTX). All of these were detected with high sensitivity, short response time, and good reproducibility.

Characterization of an array of Love-wave gas sensors developed using electrospinning technique to deposit nanofibers as sensitive layers.

The electrospinning technique has allowed that very different materials are deposited as sensitive layers on Love-wave devices forming a low cost and successful sensor array. Their excellent sensitivity, good linearity and short response time are reported in this paper. Several materials have been used to produce the nanofibers: polymers as Polyvinyl alcohol (PVA), Polyvinylpyrrolidone (PVP) and Polystirene (PS); composites with polymers as PVA+SnCl4; combined polymers as PS+Poly(styrene-alt-maleic anhydride) (PS+PSMA) and metal oxides (SnO2). In order to test the array, well-known chemical warfare agent simulants (CWAs) have been chosen among the volatile organic compounds due to their importance in the security field. Very low concentrations of these compounds have been detected by the array, such as 0.2 ppm of DMMP, a simulant of sarin nerve gas, and 1 ppm of DPGME, a simulant of nitrogen mustard. Additionally, the CWA simulants used in the experiment have been discriminated and classified using pattern recognition techniques, such as principal component analysis and artificial neural networks.

Array of Love-wave sensors based on quartz/Novolac to detect CWA simulants.

An array of Love-wave sensors based on quartz and Novolac has been developed to detect chemical warfare agents (CWAs). These weapons are a risk for human health due to their efficiency and high lethality; therefore an early and clear detection is of enormous importance for the people safety. Love-wave devices realized on quartz as piezoelectric substrate and Novolac as guiding layer have been used to make up an array of six sensors, which have been coated with specific polymers by spin coating. The CWAs are very dangerous and for safety reasons their well known simulants have been used: dimethylmethyl phosphonate (DMMP), dipropyleneglycol methyl ether (DPGME), dimethylmethyl acetamide (DMA), dichloroethane (DCE), dichloromethane (DCM) and dichloropentane (DCP). The array has been exposed to these CWA simulants detecting very low concentrations, such as 25 ppb of DMMP, a simulant of nerve agent sarin. Finally, principal component analysis (PCA) as data pre-processing and discrimination technique, and probabilistic neural networks (PNN) as patterns classification technique have been applied. The performance of the sensor array has shown stability, accuracy, high sensitivity and good selectivity to these simulants.