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

Materials design may be defined as designing materials as dynamic multilevel-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.