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data analysis and chemometrics should lead to better means of real-time analysis of complex multidimensional data arrays. Advances in computational chemistry should lead to more capabilities for virtual combinatorial and high-throughput screening, that is, selection of materials by evaluating their desirability in a computational multivariate model. Overall, gathered and analyzed combinatorial and high-throughput screening data promise to provide new opportunities for structure activity relationships analysis and for the more cost- and time-effective materials design.
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ACKNOWLEDGMENTS
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The author thanks co-workers, whose names are in the references, for their contributions. This work has been supported by US Department of Energy (Grant DEFC07-01ID14093) and by the National Institute of Standards and Technology Advanced Technology Program (Grant 70NANB9H3038).
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references
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