Structural exploration of low-energy Lennard–Jones–Gauss clusters with a genetic algorithm

The Lennard–Jones–Gauss (LJG) pair potential has been shown to model structures with diverse symmetric and topological characteristics. This extension of the well-studied Lennard–Jones potential introduces competing length scales for the energy interaction minimum, i.e., there are two distances at which atoms can be apart where they are energetically stable. Here, we report the low-energy configurations of Lennard–Jones–Gauss nanoclusters for a wide range of potential parameters and numbers of particles using a genetic algorithm. We also analyze the structural characteristics of those clusters to understand how they develop with respect to the two competing length scales. We have shown that desirable characteristics for energetic, optical and catalytic applications, such as being hollow or chiral, occur more frequently in specific parameter regions. This gives us insight both into materials design and lays the groundwork for further study into both the LJG potential and the clusters it models. Graphical abstract