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MATERIALS SCIENCE
The trial-and-error approach to finding new materials with special properties may soon become a thing of the past, thanks, in part, to computational studies carried out in Denmark. Researchers there have demonstrated a procedure, based on quantum mechanical calculations and biological modeling, that screens large numbers of candidate metallic alloys in search of highly stable ones.
Of nearly 200,000 candidate alloys, the group identified the 20 most stable compounds. The top 20 list includes Ni3Al, TiAl3, and other compounds already known to be highly stable and useful, as well as unknown and little-studied materials such as Al2Zn alloys that contain Zr, Ti, Sc, or Hf, and other compounds [Phys. Rev. Lett., 88, 255506 (2002)]. The evolutionary algorithm is an iterative process designed to search for alloys with ideal characteristics from a growing and developing population of alloys. The physicists explain that in their simulations, which were carried out many times, a set of randomly selected alloys, designated as an initial population, is allowed to "breed" and "mutate." Breeding involves choosing "parent alloys" and randomly interchanging one or two elements from each parent to give "children alloys." Mutating is simulated by replacing one element in a compound with any other element in the study. The most stable parents, children, or mutants were designated as the "fittest" alloys and allowed to survive to the next generation. The population was also screened to avoid expensive and brittle products. |
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