Nano Science and Technology Institute
Nanotech 2002 Vol. 2
Nanotech 2002 Vol. 2
Technical Proceedings of the 2002 International Conference on Computational Nanoscience and Nanotechnology
 
Chapter 1: Plenary Lectures
 

What to do with Statistical Mechanics when the Figure of Merit Cannot be Calculated: Library Design for High-Throughput Materials Development

Authors:M.W. Deem
Affilation:University of California-Los Angeles, US
Pages:13 - 15
Keywords:Monte Carlo, combinatorial chemistry, high-throughput experimentation
Abstract:By analogy with Monte Carlo algorithms, we discuss new strategies for design and redesign of libraries in high-throughput experimentation, or combinatorial chemistry. Several Monte Carlo methods are examined, including Metropolis, several types of biased schemes, and composite moves that include swapping or parallel tempering. Among them, the biased Monte Carlo schemes exhibit particular high efficiency in locating optimal compounds. The Monte Carlo strategies are compared to a genetic algorithm approach. Although the best compounds identified by the genetic algorithm are comparable to those from the better Monte Carlo schemes, the diversity of favorable compounds identified is reduced. Applications to materials discovery, small molecule discovery, and templated materials synthesis are discussed.
What to do with Statistical Mechanics when the Figure of Merit Cannot be Calculated: Library Design for High-Throughput Materials DevelopmentView PDF of paper
ISBN:0-9708275-6-3
Pages:504
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