First principles high-throughput and high precision study of point defect clusters in SiC
Title: First principles high-throughput and high precision study of point defect clusters in SiC
SNIC Project: LiU-2015-00017-60
Project Type: LiU Compute
Principal Investigator: Son Nguyen <>
Affiliation: Linköpings universitet
Duration: 2015-11-30 – 2020-12-01
Classification: 10304


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 [W.F. Koehl et al., Nature 479, 84 (2011); S. Castelletto et al., Nature Mater. 13,151 (2014); D.J. Christle et al., Nature Mater. 14, 160 (2015); M. Widmann et al., Nature Mater. 14, 164 (2015); A. Lorhmann et al. Nature Commun. 6:7783 (2015)]. In all these applications, the presence of crystalline imperfections, such as point defects including both intrinsic defects and impurities, has strong impact, either on the right way or the wrong way, on the performance of the devices. As point defects can be directly modelled 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. Avády 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 automatized construction, calculation, and prior survey of point defect clusters to find possible candidates for the identification of different defect centers seen experimentally in SiC. Once, a set of candidates is constructed, precious, highly convergent calculations 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 to the nature of the defects.