Genetic algorithms in computational materials science and engineering: simulation and design of self-assembling materials Original Research Article

We introduce here two genetic algorithms that were developed in order to aid in the design of molecules for self-assembling materials. The first constructs molecules from sets of chemical building blocks, searching for candidates that are determined by an ancillary modeling program to assemble into low-energy aggregates. The results of running this Genetic Algorithm (GA) on a set of building blocks are discussed in the context of experimental observations on molecules synthesized from these chemical components. The second genetic algorithm attempts to find the most favorable configuration of four molecules in space, as determined by an empirical molecular mechanics force field. We present the results of the application of this GA to molecules that have been studied experimentally in our laboratory. The two genetic algorithms promise to be of use not only in the context in which they are presented, but also in a wide variety of future applications in molecular design and modeling.