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  • 1MESA+ Institute for Nanotechnology, University of Twente, P.O. Box 217, 7500 AE Enschede (The Netherlands).

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We developed a new method to accurately calculate how solvents affect molecular properties. This approach improves upon existing techniques by accounting for differential polarization effects, leading to more reliable predictions for chemical reactions in solution.

Keywords:
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Area of Science:

  • Computational Chemistry
  • Theoretical Chemistry
  • Quantum Chemistry

Background:

  • Accurately modeling solvent effects is crucial for understanding chemical processes.
  • Density functional theory (DFT) methods often struggle with differential polarization effects.
  • State-specific embedding potentials offer a promising avenue for improvement.

Purpose of the Study:

  • To analyze a novel wavefunction in DFT method for including differential polarization effects.
  • To validate the supermolecular reference and assess embedding response using various wavefunction approaches.
  • To investigate the impact of different functionals on excitation energy calculations.

Main Methods:

  • Utilizing a recently proposed wavefunction in DFT method with state-specific embedding potentials.
  • Employing quantum Monte Carlo (QMC), complete-active space second-order perturbation theory (CASPT2), and coupled cluster (CC) methods.
  • Studying methylenecyclopropene and acrolein in water as test cases.

Main Results:

  • QMC, CASPT2, and CC methods yielded consistent solvatochromic shifts and embedding responses.
  • The proposed scheme corrects excitation energies from frozen environment calculations but can overshoot.
  • Using wavefunction densities to polarize the environment ameliorates overshooting.
  • Approximate kinetic-energy functionals significantly impact accuracy, more so than exchange-correlation functionals.

Conclusions:

  • The developed method effectively incorporates differential polarization effects in DFT calculations.
  • While improving upon frozen environment models, further refinement is needed to avoid overcorrection.
  • The choice of kinetic-energy functional is critical for accurate excitation energy predictions in this approach.