Tuning vacancy trapping by impurities in Si and Ge through high-throughput selection
Authors : Michael Sluydts, Michael Pieters, Jan Vanhellemont, Veronique Van Speybroeck, Stefaan Cottenier
Affiliations : Center for Molecular Modeling, Ghent, Belgium; Center for Molecular Modeling, Ghent, Belgium; Department of Solid State Sciences, Ghent, Belgium; Center for Molecular Modeling, Ghent, Belgium; Center for Molecular Modeling, Ghent, Belgium, Department of Materials Science and Engineering, Ghent, Belgium;
Resume : Due to the increased availability of computational resources, DFT calculations that used to be time-consuming can now be performed in large numbers. As a consequence, automated high-throughput screening methods have appeared, capable of generating extensive DFT-based datasets. Datasets of this size can be difficult to obtain experimentally due to the time and effort involved in lab work. Moreover, the level of control one has over a computed dataset is larger than for an experimental set. Examining these datasets allows for the discovery of global trends as well as the identification of interesting cases which can serve as a starting point for further research. In the present work we applied a high-throughput methodology to study dopant behavior in the prototype semiconductors Si and Ge. DFT-calculations were performed for 73 dopants from H to Rn (excluding the lanthanides) at 6 common positions in the Si and Ge lattices, always with full geometry optimization. The lowest-enthalpy positions were identified and compared to experiment, providing a means of validation. The same dataset was then used to determine vacancy trapping enthalpies. By formulating specific criteria for a given application, the dopants that lead to optimal vacancy traps could be selected. Such knowledge is of direct relevance to industrial processes such as Czochralski growth, where suitable vacancy traps can suppress void formation.