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Accuracy of Partial Core Corrections Using Fourier Transforms in Pseudopotential-Density Functional Theory
Journal of Chemical Theory and Computation
|November 7, 2018
Summary
Calculating partial core charge density in Fourier space can introduce significant errors in electronic structure calculations. Direct real-space computation avoids these issues, improving accuracy for materials and surfaces.
Area of Science:
- Computational physics
- Materials science
- Quantum chemistry
Background:
- Accurate electronic structure calculations rely on precise exchange-correlation functionals and pseudopotentials.
- Partial core corrections are crucial for improving the accuracy and transferability of these methods.
- A common method involves Fourier transforms to compute partial core charge density.
Purpose of the Study:
- To investigate numerical errors in exchange-correlation potentials arising from Fourier transforms of partial core charge density.
- To identify the origin of these errors and their impact on electronic structure calculations.
- To propose an alternative method for accurate computation.
Main Methods:
- Analysis of partial core charge density calculations using Fourier transforms.
- Investigation of errors in the vacuum region for low-dimensional materials and surfaces modeled with supercells.
- Comparison with direct real-space calculation of partial core charge density.
Main Results:
- Widely used Fourier-space methods can introduce sizable numerical errors in exchange-correlation potentials.
- These errors, stemming from slow decay in reciprocal space, can reach ~1 eV for Kohn-Sham energies of unoccupied states.
- Direct real-space calculation effectively avoids these Fourier transform-induced numerical errors.
Conclusions:
- Fourier transforms in partial core charge density calculations can compromise accuracy, especially in vacuum regions.
- The direct real-space approach offers a more reliable alternative for accurate electronic structure and pseudopotential calculations.
- This finding is critical for reliable modeling of advanced materials and surfaces.
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