First principles high precision study of point defect clusters in SiC
Title: First principles high precision study of point defect clusters in SiC
SNIC Project: LiU-compute-2021-49
Project Type: LiU Compute
Principal Investigator: Son Nguyen <tien.son.nguyen@liu.se>
Affiliation: Linköpings universitet
Duration: 2021-12-01 – 2022-12-01
Classification: 10304
Keywords:

Abstract

Silicon carbide (SiC) is known to have great potential in high-power, high-voltage electronics. Recently, the SiC has even shown to be a very promising material that can combine the advantages of both diamond and silicon in solid-state quantum information processing [S. Castelletto et al., Nature Mater. 13,151 (2014); M. Widmann et al., Nature Mater. 14, 164 (2015); A. Lorhmann et al. Nature Commun. 6:7783 (2015); J. Wang et al. Nature communications 9.1 (2018); S. Castelletto et al. Journal of Physics: Photonics 2.2 (2020): 022001; A. Bourassa et al. Materials 19.12 (2020)]. In all these applications, crystalline imperfections, such as point defects including both intrinsic defects and impurities, has a strong impact on the performance of the devices. As point defects can be directly modeled in first principles supercell calculations, such studies have greatly contributed to identifying and understanding the electronic structure of point defects, like substitutionals, vacancies, interstitials, antisites, and their associated complexes, especially when combining with other experimental characterization techniques such as electron paramagnetic resonance [e.g., V. Ivády et al., Mater. Sci. Forum 717-720, 205 (2012); N.T. Son et al., Phys. Rev. Lett. 109, 187603 (2012); X.T. Trinh et al., Phys. Rev. B 88, 235209 (2013)] and photoluminescence [V. Ivády et al., Phys. Rev. B 92, 115206 (2015)]. However, complexes of aggregated point defects, such as carbon-interstitial clusters that may be formed during oxidation or C-implantation and annealing processes widely used for reducing the concentration of the C vacancy - the lifetime killer defect - cause much more difficulties in understanding, as they can have numerous different configurations with complex behaviours. In this project, we apply high precision calculations of point defect clusters to find possible candidates to identify different defect centers seen experimentally in SiC. The point defect candidates are found using the high-throughput software ADAQ [J. Davidsson et al. Computer Physics Communications 269:108091 (2021)]. Once a set of candidates is found, highly convergent calculations of various properties are needed to assign the experimental observations to one of the point defect cluster configurations. After identification, additional detailed studies of the cluster’s nanostructure and electrical and optical properties provide useful insight into the nature of the defects.