In a new Science paper scientists from DTU Physics and Stanford University 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.

*Andrew J. Medford*^{1,2}, Jess Wellendorff^{1,2}, Aleksandra Vojvodic^{1}, Felix Studt^{1}, Frank Abild-Pedersen^{1}, Karsten W. Jacobsen^{3}, Thomas Bligaard^{1}, Jens K. Nørskov^{1,2,*}
Science 11 July 2014: Vol. 345 no. 6193 pp. 197-200. DOI: 10.1126/science.1253486
With the surge in density functional theory (DFT) calculations of chemical and materials properties, the question of the reliability of calculated results becomes increasingly urgent, particularly when calculations are used to make predictions of new materials with interesting functionality.

*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. 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). **Source: SLAC News*

In this paper we introduce a general method for estimating the uncertainty in calculated materials properties based on density functional theory calculations. We illustrate the approach for a calculation of the catalytic rate of ammonia synthesis over a range of transition-metal catalysts. The correlation between errors in density functional theory calculations is shown to play an important role in reducing the predicted error on calculated rates. Uncertainties depend strongly on reaction conditions and catalyst material, and the relative rates between different catalysts are considerably better described than the absolute rates. We introduce an approach for incorporating uncertainty when searching for improved catalysts by evaluating the probability that a given catalyst is better than a known standard.

**More information:**

Uncertainty Gives Scientists New Confidence in Search for Novel Materials - SLAC News July 10, 2014