Technological innovation - faster computers, more efficient solar cells, more compact energy storage - is often enabled by materials advances. Yet, it takes an average of 18 years to move new materials discoveries from lab to market. This is largely because materials designers operate with very little information and must painstakingly tweak new materials in the lab. Computational materials scienc
e is now powerful enough that it can predict many properties of materials before those materials are ever synthesized in the lab. By scaling materials computations over supercomputing clusters, we have computed some properties of over 80,000 materials and screened 25,000 of these for Li-ion batteries. The computations predicted several new battery materials which were made and tested in the lab and are now being patented. By computing properties of all known materials, the Materials Genome aims to remove guesswork from materials design in a variety of applications. Experimental research can be targeted to the most promising compounds from computational data sets. Researchers will be able to data-mine scientific trends in materials properties. By providing materials researchers with the information they need to design better, the Materials Genome aims to accelerate innovation in materials research.
