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Sascha Klawohn1, Hilke Bahmann2

  • 1Technische Universität Berlin, Institut für Chemie , Theoretische Chemie/Quantenchemie Sekretariat C7, Straße des 17. Juni 135 , 10623 Berlin , Germany.

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This summary is machine-generated.

We introduce a new method for hybrid exchange functionals using local range separation (LRS) with a position-dependent parameter. This approach improves accuracy for chemical properties and electronic spectra in larger systems.

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Area of Science:

  • Quantum Chemistry
  • Computational Materials Science
  • Electronic Structure Theory

Background:

  • Local range separation (LRS) is an established concept for hybrid functionals.
  • Previous implementations faced limitations with approximations to exact exchange.
  • Accurate modeling of chemical properties requires robust electronic structure methods.

Purpose of the Study:

  • To implement self-consistently hybrid exchange functionals with a position-dependent range-separation parameter.
  • To improve the accuracy and applicability of LRS methods for larger systems.
  • To investigate the impact of short-range exchange on the LRS scheme.

Main Methods:

  • Developed a self-consistent implementation of hybrid functionals with a position-dependent range-separation parameter.
  • Calculated two-electron integrals for long-range exact exchange seminumerically, avoiding approximations.
  • Proposed and optimized a semiempirical range-separation function based on semilocal exchange-correlation functional ingredients.

Main Results:

  • The new LRS functional performs well for basic chemical properties compared to established methods.
  • Outer-valence spectra obtained with the best functional are comparable to optimally tuned approaches.
  • The seminumerical calculation of integrals enables applications to larger, chemically relevant systems.

Conclusions:

  • The developed LRS scheme offers a promising avenue for accurate and efficient electronic structure calculations.
  • This method provides a balance between accuracy and computational cost for various chemical applications.
  • The findings pave the way for broader adoption of LRS in computational chemistry.