For five years, the National Institute of Standards & Technology (NIST) has been developing a computational tool for analyzing and predicting the performance of solid materials with complex microstructures. OOF -- it rhymes with "goof -- " is the public-domain program that has resulted from this effort. Before the development of OOF, researchers were limited to studying the properties of either simple materials or idealized models of more complex materials. Using OOF, they can scan a micrograph -- a photograph of an actual material on a microscopic scale -- into a computer and turn it into a digital image. Then, using OOF's intuitive graphical interface, they can point and click on subregions of the micrograph. Based on the geometry of these subregions, OOF allows users to develop a comprehensive analysis and prediction of how the material will respond to heat, stress, and other forces. "Before the development of this program, people could see the microstructures but had limited means of understanding how they led to certain mechanical properties," says Geoffrey McFadden, group leader for mathematical modeling in NIST's Mathematical & Computational Sciences Div. "OOF shows the relationship between what you observe on a very small scale and what you can measure on a very large scale." The OOF advantage to corporate R&D could be significant. Because OOF replaces weeks of laboratory experiments with quick computational assays, it can help researchers run their labs more strategically. "Laboratory work has become very expensive due to the rising costs of materials, equipment, and personnel," says Katherine Faber, professor of materials science and engineering at Northwestern University, Evanston, Ill., who is using OOF to study brittle materials such as ceramics. "OOF points researchers toward the right experiments to do in the lab." John Teresko, John Sheridan, Tim Stevens, Doug Bartholomew, Patricia Panchak, Tonya Vinas, Samuel Greengard, Kristin Ohlson, and Barbara Schmitz contributed to this article.