Recognition of a hidden mineral deposit by an artificial intelligence program

A computer program that uses artificial intelligence techniques has successfully identified the location of a porphyry molybdenum deposit. Given geological maps of readily available predrilling exploration data for Mount Tolman in Washington State and using rules obtained from a porphyry molybdenum exploration specialist, the program (called PROSPECTOR) identified the location of previously unknown ore-grade mineralization. This appears to be the first reported determination of the location of mineralization by such a computer-based approach.     

Implications for mantle dynamics from the high melting temperature of perovskite

Recent studies have implied that (Mg, Fe)SiO(3)-perovskite, a likely dominant mineral phase in the lower mantle, may have a high melting temperature. The implications of these findings for the dynamics of the lower mantle were investigated with the use of numerical convection models. The results showed that low homologous temperatures (0.3 to 0.5) would prevail in the modeled lower mantle, regardless of the effective Rayleigh number and internal heating rates. High-temperature ductile creep is possible under relatively cold conditions. In models with low rates of internal heating, local maxima of viscosity developed in the mid-lower mantle that were similar to those obtained from inversion of geoid, topography, and plate velocities.