Abstract
We present an efficient and accurate method for designing materials for electronic applications. Our approach is to search an atomic configuration space by repeatedly applying a forward solver, guiding the search toward the optimal configuration using an evolutionary algorithm. We employ a hierarchical parallelism for the combined forward solver and the genetic algorithm. This enables the optimization process to run on many more processors than would otherwise be possible. We have optimized AlGaAs alloys for maximum bandgap and minimum bandgap for several given compositions. When combined with an efficient forward solver, this approach can be generalized to a wide range of applications in material design.
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