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Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry
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Optimizing conical intersections without derivative coupling vectors: application to multistate multireference

Benjamin G Levine1, Joshua D Coe, Todd J Martínez

  • 1Department of Chemistry and The Beckman Institute, University of Illinois, Urbana, Illinois 61801, USA.

The Journal of Physical Chemistry. B
|December 18, 2007
PubMed
Summary

We present a novel method for optimizing minimal energy conical intersections (MECIs) using sequential penalty optimization. This approach enhances the accuracy of calculating molecular geometries and energies for conjugated systems.

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Area of Science:

  • Computational Chemistry
  • Quantum Chemistry
  • Theoretical Chemistry

Background:

  • Conical intersections are crucial for understanding photochemical reactions and spectroscopy.
  • Efficient methods are needed to locate and optimize these critical points on potential energy surfaces.

Purpose of the Study:

  • To develop and validate a new computational method for optimizing minimal energy conical intersections (MECIs).
  • To introduce the concept of "minimal distance conical intersections" for targeted geometry searches.

Main Methods:

  • Sequential penalty constrained optimization with a smoothing function.
  • Application of the multistate formulation of second-order multireference perturbation theory (MS-CASPT2).
  • Comparison with state-averaged complete active space self-consistent field (SA-CASSCF) and MRSDCI methods.

Main Results:

  • Optimized MECI geometries and energetics for various conjugated molecules.
  • Validation of the new method against established computational techniques.
  • Demonstration of the "minimal distance conical intersection" concept.

Conclusions:

  • The developed method provides an efficient and accurate approach for MECI optimization.
  • The "minimal distance conical intersection" offers a new perspective for analyzing excited-state dynamics.