Multicomponent gas-mixture measurements using an array of gas sensors and an artificial neural-network

An Electronic Nose is being jointly developed between the University of Greenwich and the Institute of Intelligent Machines to detect the gases given off from an oil filled transformer when it begins to break down. The gas sensors being used are very simple, consisting of a layer of Tin Oxide (SnO2) which is heated to approximately 640 K and the conductivity varies with the gas concentrations. Some of the shortcomings introduced by the commercial gas sensors available are being overcome by the use of an integrated array of gas sensors and the use of artificial neural networks which can be 'taught' to recognize when the gas contains several components. At present simulated results have achieved up to a 94% success rate of recognizing two component gases and future work will investigate alternative neural network configurations to maintain this success rate with practical measurements.

Structural and biological investigation of ferrocene-substituted 3-methylidene-1,3-dihydro-2H-indol-2-ones

The Knoevenagel condensation of 1,3-dihydro-2H-indol-2-one with ferrocene carboxaldehyde afforded an approximate 2:1 mixture of the geometrical isomers (E)- and (Z)-3-ferrocenylmethylidene-1,3-dihydro-2H-indol-2-one respectively in an overall 67% yield; the air and solution-stable isomers were readily separated by preparative thin layer chromatography and their structures were unequivocally elucidated in solution, by (1)H NMR spectroscopy, and in the solid phase, by X-ray crystallography; both isomers of displayed in vitro toxicity against B16 melanoma and Vero cell lines in the micromolar range and inhibited the kinase VEGFR-2 with IC(50) values of ca. 200 nM.