Improving fuel production
Researchers using the supercomputing resources at the Argonne Leadership Computing Facility (ALCF) have demonstrated a predictive modeling capability that can help accelerate the discovery of new materials to improve biofuel and petroleum production.
The findings, recently published in Nature Communications, present a tool that could lead to more efficient processes in the biofuel and petrochemical industries, while reducing the time and cost of associated laboratory research and development efforts.
Peng Bai, Mi Young Jeon, Limin Ren, Chris Knight, Michael W. Deem, Michael Tsapatsis and J. Ilja Siepmann, “Discovery of Optimal Zeolites for Challenging Separations and Chemical Transformations Using Predictive Materials Modeling,” Nature Communications 6, Article Number: 5912. DOI:10.1038/ncomms6912, Published January 21, 2015.