Uncertainty gives scientists new confidence in search for novel materials

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Scientists at Stanford University and the Department of Energy’s SLAC National Accelerator Laboratory have found a way to estimate uncertainties in computer calculations that are widely used to speed the search for new materials for industry, electronics, energy, drug design and a host of other applications. The technique, reported in the July 11 issue of Science, should quickly be adopted in studies that produce some 30,000 scientific papers per year. This image shows the results of calculations aimed at determining which of six chemical elements would make the best catalyst for promoting an ammonia synthesis reaction. Researchers at SLAC and Stanford used Density Functional Theory (DFT) to calculate the strength of the bond between nitrogen atoms and the surfaces of the catalysts. The bond strength, plotted on the horizontal axis, is a key factor in determining the reaction speed, plotted on the vertical axis. Based on thousands of these calculations, which yielded a range of results (colored dots) that reveal the uncertainty involved, researchers estimated an 80 percent chance that ruthenium (Ru, in red) will be a better catalyst than iron (Fe, in orange.) (Andrew Medford and Aleksandra Vojvodic/SUNCAT, Callie Cullum) “Over the past 10 years our ability to calculate the properties of

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