Continuous flow gas phase photoreforming of methanol at elevated reaction temperatures sensitised by Pt/TiO2

Gas phase photoreforming of methanol using a Pt/TiO2 photocatalyst has been performed under flow conditions at elevated temperatures. Comparing the activity of the reforming process as a function of temperature under dark and irradiated conditions shows a significant enhancement in the rate of H2 production using the photo-assisted conditions at temperatures between 100-140 °C. At higher temperatures, the effect of irradiation is small with the process dominated by the thermal process. Deactivation of the catalyst was observed under irradiation but the catalyst was easily regenerated using an oxygen treatment at 120 °C. Diffuse Reflectance Infra-red Fourier Transform Spectroscopy (DRIFTS) showed that the activity of the catalyst could be correlated with the presence of the photogenerated trapped electrons. In addition, lower amounts of CO adsorbed on Pt, compared to those observed in the dark reaction, were found for the UV-irradiated systems. It is proposed that CO and adsorbed intermediates, such as formate, can act as inhibitors in the photoreforming process and this is further supported by the observation that, before and after the regeneration process in O2, the CO and surface adsorbed organic intermediate products are removed and the activity is recovered.

Continuous statistical modelling for rapid detection of adulteration of extra virgin olive oil using mid infrared and Raman spectroscopic data

The main objective of this work was to develop a novel dimensionality reduction technique as a part of an integrated pattern recognition solution capable of identifying adulterants such as hazelnut oil in extra virgin olive oil at low percentages based on spectroscopic chemical fingerprints. A novel Continuous Locality Preserving Projections (CLPP) technique is proposed which allows the modelling of the continuous nature of the produced in-house admixtures as data series instead of discrete points. The maintenance of the continuous structure of the data manifold enables the better visualisation of this examined classification problem and facilitates the more accurate utilisation of the manifold for detecting the adulterants. The performance of the proposed technique is validated with two different spectroscopic techniques (Raman and Fourier transform infrared, FT-IR). In all cases studied, CLPP accompanied by k-Nearest Neighbors (kNN) algorithm was found to outperform any other state-of-the-art pattern recognition techniques.