Rough Sets Applied to the Discovery of Materials Knowledge

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The functional mapping of material structure to properties, processing, and use is the principal driver for all scientific and engineering endeavors. Given the high cost of experimentation and the computational intractability of ab initio materials research, more efficient and accurate predictions of yet-to-be-made materials is an equally prominent endeavor, if not a preeminent materials research frontier. Because of the vast amounts of information to be considered in the pursuit of either, the automation of search-based methods for augmenting more analytic approaches is receiving increasing attention. Given the computational challenges to automation and to retrieving data from complex databases, search-based methods offer an expeditious approach to providing a researcher both insight and perspective. Rough sets is discussed relative to these objectives, as is current research to address its limitations and difficulties in application. Several materials related examples are offered to illustrate the application of the method.



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