In a study published in Nature Communications, researchers developed a computational protocol to optimize the yield of silicon carbide spin defects at the atomistic level, determining the optimal annealing temperature and Fermi level engineering.
Pictorial representation of the complex free energy surface of the double vacancy in SiC (Si and C atoms are represented by blue and brown spheres, respectively) on top of a SiC wafer.
Scientific Achievement
We devised a computational protocol to investigate the synthesis of point-defects at the atomistic level. We determined the optimal annealing temperature and predicted how to engineer the Fermi level of silicon carbide (SiC) to optimize the yield of double vacancies, that are promising spin defects for quantum technologies.
Significance and Impact
The computational protocol is general and applicable to a broad category of spin defects. Our calculations highlighted the importance of sampling non equilibrium and metastable states as a function of T to obtain robust predictions and led to the interpretation of controversial experimental results.
Research Details
- Combined first principles density functional theory and nonrelativistic quantum electrodynamics to derive energy transfer amplitudes in the near field.
- Carried out simulations with variable charge and spin states.