Fully-Optimized Parameters for Mixed Ramp-Gaussian Basis Sets.

Area of Science:

• Computational quantum chemistry
• Theoretical chemistry
• Materials science

Background:

• Accurate description of core electrons is crucial for predicting chemical properties.
• Traditional all-Gaussian basis sets exhibit deficiencies in describing core electronic wave functions, limiting accuracy and increasing computational cost.
• Mixed ramp-Gaussian basis sets present a potential alternative, but previous attempts at optimization have yielded limited success.

Purpose of the Study:

• To introduce and parametrize novel, fully optimized mixed ramp-Gaussian basis sets, termed R_S-n.
• To evaluate the performance of these new basis sets for calculating core-dependent properties.
• To confirm the significance of optimizing nonpolarization Gaussian functions within mixed basis sets.

Main Methods:

• Development of R_S-n basis sets using pseudo ramp functions to approximate ramp functions.
• Parametrization of fully optimized mixed ramp-Gaussian basis sets.
• Extensive benchmark studies to assess basis set performance.

Main Results:

• The R_S-n basis sets demonstrate significant promise for the efficient calculation of core-dependent properties.
• Full optimization of nonpolarization Gaussian functions is critical for the performance of mixed ramp-Gaussian basis sets.
• The new basis sets show improved accuracy and efficiency compared to traditional Gaussian sets for core-electron descriptions.

Conclusions:

• Fully optimized mixed ramp-Gaussian basis sets (R_S-n) are effective for computational chemistry.
• These basis sets address limitations of traditional Gaussian sets in describing core electrons.
• R_S-n basis sets offer a promising avenue for accurate and efficient computation of chemical properties.