The behaviour of H2 and O2 flows over a porous P-Cr2O3 pellet have been studied by means of an in situ electrical conductivity technique. Changes in the electrical conductivity associated with such gas flows were attributed to changes in the concentration of positively charged holes in the material studied. In the presence of an H2 flow, the electrical conductivity of the p-Cr2O3 surface first increased and then decreased sharply. The initial increase was attributed to the chemisorption of H2 leading to surface hydroxylation. The formation of O-H bonds during this process resulted in a decrease in the electron density at the surface and thereby increased the contribution of positively charged holes towards the total conductivity. In contrast, the subsequent sharp decrease in conductivity was explained by the elimination of chemisorbed oxygen which had originally been adsorbed dissociatively at the surface. During this process, elimination of chemisorbed oxygen atoms led to the presence of electrons in the chromia lattice which generated a sharp decrease in the hole concentration via an electron-hole recombination process. In an O2 atmosphere, the conductivity of the deoxygenated chromia increased exponentially to a maximum value and then decreased until it reached a value similar to that for stoichiometric chromia. The increase in conductivity observed in this case was assigned to the adsorption of oxygen on the chromia surface while the subsequent decrease was attributed to hydrogen desorption. The kinetics of the four processes observed, i.e. hydrogen adsorption, oxygen desorption, oxygen adsorption and hydrogen desorption, have been analyzed.

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{Reliability has emerged as significant issue in developing of expert systems. Verification plays an important role in assuring the reliability of expert systems. Expert systems verification involves checking the knowledge base for consistency, completeness, and other errors. Our study indicates that in order to verify an expert system, it is necessary to have a conceptual model of the knowledge base. The KADS methodology lends itself to conceptual modeling of the knowledge base, This enabled us to build an automatic verification tool. This tool is able to detect different knowledge base error types. A novel feature of this tool is its ability to detect consistency errors that arise due to using KADS methodology in knowledge modeling.}