  Under irradiation, SiC develops damage commonly referred to as black spot
defects, which are speculated to be self-interstitial atom clusters. To
understand the evolution of these defect clusters and their impacts (e.g.,
through radiation induced swelling) on the performance of SiC in nuclear
applications, it is important to identify the cluster composition, structure,
and shape. In this work the genetic algorithm code StructOpt was utilized to
identify groundstate cluster structures in 3C-SiC. The genetic algorithm was
used to explore clusters of up to ~30 interstitials of C-only, Si-only, and
Si-C mixtures embedded in the SiC lattice. We performed the structure search
using Hamiltonians from both density functional theory and empirical
potentials. The thermodynamic stability of clusters was investigated in terms
of their composition (with a focus on Si-only, C-only, and stoichiometric) and
shape (spherical vs. planar), as a function of the cluster size (n). Our
results suggest that large Si-only clusters are likely unstable, and clusters
are predominantly C-only for n <= 10 and stoichiometric for n > 10. The results
imply that there is an evolution of the shape of the most stable clusters,
where small clusters are stable in more spherical geometries while larger
clusters are stable in more planar configurations. We also provide an estimated
energy vs. size relationship, E(n), for use in future analysis.
