OEIT Collaborates with Civil and Environmental Engineering

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OEIT Collaborates with Civil and Environmental Engineering to Help Students in 1.978 Visualize Nanoscale Problems---Software designed for genetics shows how materials behave under extreme loading

This has been excerpted from a news item that appeared in the April 2, 2007 issue of MIT News, see http://web.mit.edu/newsoffice/2007/atomistic.html. A version of this article also appeared in MIT Tech Talk on April 11, 2007.

An educational experiment during IAP demonstrated that students can learn to apply sophisticated atomistic modeling techniques to traditional materials research in just a few classes, an advance that could dramatically change the way civil engineers learn to model the mechanical properties of materials and provide enormous benefit to industry.

"Taking an atomistic approach to the study of materials' design and analysis offers opportunities for making significant improvements in materials' strength, reliability and sustainability," said Markus Buehler, an assistant professor in the Department of Civil and Environmental Engineering who collaborated with Ivica Ceraj, a software developer in MIT's Office of Educational Innovation and Technology (OEIT), to prepare the new simulation techniques.

"While scientists often rely on quantum mechanics in their study of materials, engineers tend to use a more traditional continuum approach that relies on empirical parameters to model processes such as a crack forming, without considering the mechanisms at the atomic scale that give rise to these phenomena," said Buehler. The problem Buehler faced was finding a way to teach students to model the material's atomic response without getting too caught up in the complexities of a computer program.

This is where Ceraj and the OEIT initiative came in. "We are looking to reduce the operational fog and help students focus on the subject they are learning without stumbling over new software tools," said Ceraj.

Buehler and Ceraj employed a web interface called GenePattern, an award-winning software program developed in 2004 by a team at the Broad Institute of MIT and Harvard to help scientists perform gene expression analysis. Ceraj created an interface between GenePattern and the software code Buehler uses in his own research. The interface, a derivative application that Ceraj calls StarGP, provides a simple-to-use, yet very accurate tool for modeling the behavior of materials under extreme loading.

In Course 1.978 (From Nano to Macro: Introduction to Atomistic Modeling Techniques), Ceraj and Buehler introduced students to the new atomistic simulation program with great success. They found that when using the web interface method, students learned the basics of atomistic modeling quickly, and then applied the technique to predict the mechanical properties of silicon, copper nanowire and a structural protein called vimentin that plays a crucial role in stabilizing eukaryotic cells under deformation.

As a result of the class, students not only learned the atomistic simulation quickly, some have already adopted it for their own applications. Michelle Hyers, who is working toward a Ph.D. in mechanical engineering, took the class to find a more accurate way of modeling at smaller scales. "My research involves modeling self-assembly at the micro and nanoscales, but we currently use macroscale theory with various assumptions to describe the system," said Hyers. "As a result of this class, I formed collaboration with Professor Buehler to work on a more accurate model for our system than our current approximate methods." She added, "It is the best class I've had so far at MIT in terms of engaging content, as well as excellent teaching."

Buehler plans to use this method next spring to teach a section of Course 1.021J (Introduction to Modeling and Simulation), an undergraduate class that provides an overview of simulation techniques. This subject will expose undergraduates to state-of-the-art atomistic modeling methods to teach the next generation of engineers how to make a big impact by thinking small.