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Time-dependent density functional theory for nonlinear properties of open-shell systems.

Zilvinas Rinkevicius1, Prakash Chandra Jha, Corneliu I Oprea

  • 1Department of Theoretical Chemistry, Royal Institute of Technology, S-106 91 Stockholm, Sweden.

The Journal of Chemical Physics
|September 25, 2007
PubMed
Summary

This study introduces a new computational method for calculating molecular properties, particularly for systems with high spin ground states. The findings support the role of silicon surface defects in second harmonic generation phenomena.

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Area of Science:

  • Computational Chemistry
  • Quantum Mechanics
  • Materials Science

Background:

  • Nonlinear optical properties are crucial for materials applications.
  • Accurate computation of these properties for open-shell systems remains challenging.
  • Silicon surfaces, especially with defects, are technologically relevant.

Purpose of the Study:

  • To develop a robust theoretical framework for calculating nonlinear properties of molecules with high spin ground states.
  • To investigate the role of silicon surface defects in second harmonic generation.
  • To assess the computational requirements for accurate predictions.

Main Methods:

  • Development of a spin-restricted Kohn-Sham formalism for response theory.
  • Application to compute static and dynamic hyperpolarizabilities.
  • Calculations performed on Si(3n+1)H(6n+3) clusters mimicking Si(111) surfaces.

Main Results:

  • The proposed method efficiently computes electric, magnetic, and mixed properties.
  • Calculated hyperpolarizabilities of Si(3n+1)H(6n+3) clusters align with experimental observations of second harmonic generation.
  • Results highlight the necessity of diffuse basis sets and appropriate functionals for open-shell compounds.

Conclusions:

  • The computational approach is effective for high spin systems.
  • Silicon dangling bond defects are likely responsible for observed second harmonic generation at SiO2/Si(111) interfaces.
  • Accurate prediction of hyperpolarizability requires careful selection of computational parameters.