Polarized Neutron Reflectometry of Nickel Corrosion Inhibitors.

Polarized neutron reflectometry has been used to investigate the detailed adsorption behavior and corrosion inhibition mechanism of two surfactants on a nickel surface under acidic conditions. Both the corrosion of the nickel surface and the structure of the adsorbed surfactant layer could be monitored in situ by the use of different solvent contrasts. Layer thicknesses and roughnesses were evaluated over a range of pH values, showing distinctly the superior corrosion inhibition of one negatively charged surfactant (sodium dodecyl sulfate) compared to a positively charged example (dodecyl trimethylammonium bromide) due to its stronger binding interaction with the surface. It was found that adequate corrosion inhibition occurs at significantly less than full surface coverage.X-ray photoelectron spectra were obtained at the National Engineering and Physical Sciences Research Council (EPSRC) XPS User’s Service (NEXUS) at Newcastle University, an EPSRC midrange facility. NR data were obtained on the D17 instrument, and samples were treated in the laboratories of the Partnership for Soft Condensed Matter (PSCM) at the Institut Laue-Langevin. M.H.W. is grateful for funding from the Oppenheimer Trust.This is the final version of the article. It first appeared from the American Chemical Society via http://dx.doi.org/10.1021/acs.langmuir.5b0171

A Tool for Automatic Creation of Rule-Based Expert Systems with CFs

International audienceThis paper introduces a tool, namely ACRES (Automatic CReator of Expert Systems), which can automatically produce rule-based expert systems as CLIPS scripts from a dataset containing knowledge about a problem domain in the form of a large number of cases. The rules are created via a simple systematic approach and make use of certainty factors (CFs). CFs of same conclusions can be combined either using the MYCIN method or a generalization of MYCIN's method. This latter method requires calculation of some weights, based on a training dataset, via the use of a genetic algorithm. Creation of an expert system is outlined. Small scale experimental results comparing the above methods with each other and a neural network are finally presented