By reworking a theory first proposed by physicists in the 1920s, the researchers discovered a new way to predict important characteristics of a new material before it's been created. The new formula allows computers to model the properties of a material up to 100,000 times faster than previously possible and vastly expands the range of properties scientists can study.
"The equation scientists were using before was inefficient and consumed huge amounts of computing power, so we were limited to modeling only a few hundred atoms of a perfect material," said Emily Carter, the engineering professor who led the project.
"But most materials aren't perfect," said Carter, the Arthur W. Marks '19 Professor of Mechanical and Aerospace Engineering and Applied and Computational Mathematics. "Important properties are actually determined by the flaws, but to understand those you need to look at thousands or tens of thousands of atoms so the defects are included. Using this new equation, we've been able to model up to a million atoms, so we get closer to the real properties of a substance."
By offering a panoramic view of how substances behave in the real world, the theory gives scientists a tool for developing materials that can be used for designing new technologies. Car frames made from lighter, strong metal alloys, for instance, might make vehicles more energy efficient, and smaller, faster electronic devices might be produced using nanowires with diameters tens of thousands of times smaller than that of a human hair.
Janos Haits on 02 Apr 12Come work with us Interested in working with researchers from different disciplines within the Harvard, MIT and Broad community and an unique opportunity to participate in world-class research to make an impact on human health? Come work with us! We are looking for a computational biologists to handle data from a wide variety of experimental methods, focusing on next-gen sequencing technologies. Keep Reading... SCDE is live The Stem Cell Discovery Engine (SCDE) is an integrated platform that allows users to consistently describe, share and compare cancer and tissue stem cell data. It is made up of an online database of curated experiments coupled to a customized instance of the Galaxy analysis engine with tools for gene list manipulation and molecular profile comparisons. The SCDE currently contains more than 50 stem cell-related experiments. Each has been manually curated and encoded using the ISA-Tab standard to ensure the quality of the data and its annotation. Keep Reading... The Center for Health Bioinformatics at the Harvard School of Public Health provides consults to researchers for the management, integration and contextual analysis of biological high-throughput data. We are a member of the Center for Stem Cell Bioinformatics, the Environmental Statistics and Bioinformatics Core at the Harvard NIEHS Center for Environmental Health and the Genetics & Bioinformatics Consulting group for Harvard Catalyst and work closely with our colleagues in the Department of Biostatistics and the Program in Quantitative Genomics to act as a single point of contact for computational biology,
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