Polypyrrole (PPy) nanorods (NRs) and nanoparticles (NPs) are synthesized via electrochemical and chemical methods, respectively, and tested upon ammonia exposure using Raman and X-ray photoelectron spectroscopy (XPS). Characterization of both nanomaterials via Raman spectroscopy demonstrates the formation of PPy, displaying vibration bands consistent with the literature. Additionally, XPS reveals the presence of neutral PPy species as major components in PPy NRs and PPy NPs, and other species including polarons and bipolarons. Raman and XPS analysis after ammonia exposure show changes in the physical/chemical properties of PPy, confirming the potential of both samples for ammonia sensing. Results demonstrate that the electrochemically synthesized NRs involve both proton and electron transfer mechanisms during ammonia exposure, as opposed to the chemically synthesized NPs, which show a mechanism dominated by electron transfer. Thus, the different detection mechanisms in PPy NRs and PPy NPs appear to be connected to the particular morphological and chemical composition of each film. These results contribute to elucidate the mechanisms involved in ammonia detection and the influence of the synthesis routes and the physical/chemical characteristics of PPy.

A new method of synthesising nanoparticle-functionalised nanostructured materials via Aerosol Assisted Chemical Vapour Deposition (AACVD) has been developed. Co-deposition of Au nanoparticles with WO₃ nanoneedles has been used to deposit a sensing layer directly onto gas sensor substrates providing devices with a six-fold increase in response to low concentrations of a test analyte (ethanol).

The field of electronic noses, electronic instruments capable of mimicking the human olfactory system, has developed rapidly in the past ten years. There are now at least 25 research groups working in this area and more than ten companies have developed commercial instruments, which are mainly employed in the food and cosmetics industries. Most of the work published to date, and commercial applications, relate to the use of well established static pattern analysis techniques, such as principal components analysis, discriminant function analysis, cluster analysis and multilayer perceptron based neural networks. The authors first review static techniques that have been applied to the steady-state response of different odour sensors, e.g. resistive, acoustic and FET-based. Then they review the emerging field of the dynamic analysis of the sensor array response. Dynamic signal processing techniques reported so far include traditional parametric and nonparametlic ones borrowed from the traditional field of system identification as well as linear filters, time series neural networks and others. Finally the authors emphasise the need for a systems approach to solve specific electronic nose applications, with associated problems of sensor diift and interfesence.