General Electric Company

Martha Gardner

Larry Neil Lewis

Rajesh Tyagi

John Matthew Bablin

Thomas Paul Repoff

David Cheney DeMoulpied

Abhinanda Sarkar

William Jessup Ward

Angshuman Saha

Malcolm Craig Winslow

Michael Dion

Shirley Au

Roy Wilson

A method and system for assessing and optimizing crude selection are provided. A predictive engine uses data from a database to execute at least one predictive performance model and/or at least one risk assessment model designed to optimize or improve refining operations during a refining process. The predictive engine takes as input key crude information corresponding to a particular crude or crude blend, e.g., at least one crude slate, and refinery operating parameters and/or conditions corresponding to a specific refinery and uses desirability metrics to assess the similarity to data in the database. Based on the resulting output, at least one predictive performance and/or at least one risk assessment model uses the output to predict performance or risk measures of refining the particular crude or crude blend using the specific refinery during the refining process, the probability of problems occurring during the refining process, the distribution of the problems throughout the refining process, etc.

Method and system for assessing and optimizing crude selection

Dialkyldihalosilane formation during direct method alkylhalosilane production is promoted by effecting reaction between alkyl halide and powdered silicon in the presence of a catalyst comprising copper, zinc, and aluminum and further comprising an amount of phosphorus and tin wherein the amount of phosphorus and tin substantially enhances the selectivity of dialkyldihalosilane formation in comparison to the selectivity of dialkyldihalosilane formation in the presence of the catalyst comprising copper, zinc, aluminum and tin without phosphorus.

Method for promoting dialkyldihalosilane formation during direct method alkylhalosilane production

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Niskayuna, NY, United States of America

Martha Gardner