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A general-purpose Density Functional Tight Binding method, the GFN-xTB modelis gaining increased popularity in accurate simulations that are out of scopefor conventional ab initio formalisms. We show that in its original GFN1-xTBparametrization, organosilicon compounds are described poorly. This issue isaddressed by re-fitting the model's silicon parameters to a data set of tenthousand reference compounds, geometry-optimized with the revPBE functional.The resulting GFN1-xTB-Si parametrization shows improved accuracy in theprediction of system energies, nuclear forces and geometries and should beconsidered for all applications of the GFN-xTB Hamiltonian to systems thatcontain silicon.

Improving the Silicon Interactions of GFN-xTB