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Introducing genetic algorithms as a reliable and efficient tool to findordered equilibrium structures, we predict minimum energy configurations of thesquare shoulder system for different values of corona width $\lambda$. Varyingsystematically the pressure for different values of $\lambda$ we obtaincomplete sequences of minimum energy configurations which provide a deeperunderstanding of the system's strategies to arrange particles in anenergetically optimized fashion, leading to the competing self-assemblyscenarios of cluster-formation vs. lane-formation.

Lane-formation vs. cluster-formation in two dimensional square-shoulder systems: A genetic algorithm approach