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Cohn says that the aim of his work is to bridge this gap between theory and reality. Previous versions of these algorithms have generated very complex instructions for putting together these structures, stipulating that a very large number of parameters need to be met in order to get a structure to assemble. “If you’re allowed to make elaborate potential functions, you can do elaborate things” and make wonderful materials inside the computer, he says. Now the question for theorists, Cohn says, is “Can we achieve more using simpler interactions?”

The Microsoft and MIT researchers have taken an important step toward this simplification, says Salvatore Torquato, a professor of chemistry at the Princeton Institute for the Science and Technology of Materials. Their models require a much smaller number of these potential-energy relationships than did previous ones. “That takes it from very hypothetical to something more realistic to produce in the laboratory,” says Torquato. The sophistication of the Microsoft model comes in part from introducing ideas from information theory.

The next step is to work with chemists to create one of these predicted structures in the lab. “I believe the materials science of the future will be done this way,” Torquato says of computer modeling. Whitesides believes that the theorists are still far from realizing that future because it’s still unclear whether the types of functions being developed by Cohn can be used to make self-assembling structures at all, or whether some other theoretical approach will turn out to be more useful. But work on these types of algorithms, says Whitesides, “is worth pursuing, since the resulting shouting match will help define what needs to be done” to make them useful.

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Credit: Salvatore Torquato

Tagged: Computing, Materials, Microsoft, photonics, self-assembly, science, computer science, computer models

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