4.5 Article Proceedings Paper

Tailor-made material design: An evolutionary approach using multi-objective genetic algorithms

期刊

COMPUTATIONAL MATERIALS SCIENCE
卷 45, 期 1, 页码 1-7

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.commatsci.2008.03.057

关键词

Optimization; Materials design; Inter-atomic potential; Stiffness; Lightness; Lennard-Jones potential; Multi-objective genetic algorithms; NSGA-II

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Materials design may be defined as designing materials as dynamic multi level-structured systems with integrated and specific process/structure/performance/property relationships. The main objective of the work is to design structural materials based on inter-atomic potentials - the so-called inverse problem - to explore materials of high strength to weight ratio with a thermodynamically stable structure. Since the aforementioned objectives are contradicting each other it leads to a Pareto-optimal problem which is eventually solved by the multi-objective genetic algorithms solver NSGA-II. The material behavior is modeled using Lennard-Jones type interatomic potential function. The Pareto-optimal front provides a series of hypothetical materials which are then compared and contrasted with existing materials as and when possible. (C) 2008 Elsevier B.V. All rights reserved.

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