only the fittest survive to catalyze another reaction

RESEARCH NEWS February 2002 9 Chemical engineers from Purdue University have developed a new method for creating catalytic materials. Combining artificial intelligence with combinatorial chemistry, the technique can test thousands of formulations simultaneously to speed up the discovery process. The same method could also be used for many types of materials research, says one of the scientists responsible Jochen Lauterbach. Described at the recent International Symposium on Combinatorial Approaches for New Materials Discovery in San Diego, the automated system systematically creates and tests multiple samples in parallel. Nanoscale plastic beads are coated with different catalyst materials and their performance screened using infrared sensor technology. "If a mixture doesn't work, the information about why it does not work is just as valuable as the information about why it does work," says Lauterbach. "We feed that information back into the software, and at some point we tell the program that we want a catalyst that does this and that. The software does its thing and it spits out a material combination, a range of completely new catalysts that nobody has ever thought of before, or had dared to even propose or synthesize because everybody would say, 'You've got to be crazy. This is never going to work.' It's something that is totally out-of- the-box thinking for typical catalyst development." The software includes hybrid neural networks and genetic algorithms, which make up a repeating two-phase cycle of discovery. The hybrid neural network analyzes the structures and properties of the catalysts, mimicking the thought processes of formulation chemists, says James M. Caruthers, who developed the software with Venkat Venkatasubramanian. Genetic algorithms eliminate the worst catalysts, choose the best, and generate 'mutations' to create new versions. The information is plugged back into the neural networks and the process continues. The researchers are already working with several companies – and found a potential new catalyst in 30 minutes that could have taken months to discover using traditional methods. Only the fittest survive to catalyze another reaction

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Page 1: Only the fittest survive to catalyze another reaction

RESEARCH NEWS

February 2002 9

Chemical engineers fromPurdue University havedeveloped a new method forcreating catalytic materials. Combining artificial intelligencewith combinatorial chemistry,the technique can testthousands of formulationssimultaneously to speed up thediscovery process. The samemethod could also be used formany types of materialsresearch, says one of thescientists responsible JochenLauterbach. Described at the recentInternational Symposium onCombinatorial Approaches forNew Materials Discovery in

San Diego, the automatedsystem systematically createsand tests multiple samples inparallel. Nanoscale plasticbeads are coated with differentcatalyst materials and theirperformance screened usinginfrared sensor technology. "If a mixture doesn't work, theinformation about why it doesnot work is just as valuable asthe information about why itdoes work," says Lauterbach."We feed that information backinto the software, and at somepoint we tell the program thatwe want a catalyst that doesthis and that. The softwaredoes its thing and it spits out a

material combination, a rangeof completely new catalyststhat nobody has ever thoughtof before, or had dared toeven propose or synthesizebecause everybody would say,'You've got to be crazy. This isnever going to work.' It'ssomething that is totally out-of-the-box thinking for typicalcatalyst development."The software includes hybridneural networks and geneticalgorithms, which make up arepeating two-phase cycle ofdiscovery. The hybrid neuralnetwork analyzes thestructures and properties ofthe catalysts, mimicking the

thought processes offormulation chemists, saysJames M. Caruthers, whodeveloped the software withVenkat Venkatasubramanian.Genetic algorithms eliminatethe worst catalysts, choosethe best, and generate'mutations' to create newversions. The information isplugged back into the neuralnetworks and the processcontinues. The researchersare already working withseveral companies – and founda potential new catalyst in 30 minutes that could havetaken months to discover usingtraditional methods.

Only the fittest survive to catalyze another reaction

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