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Smooth heuristic optimization on a complex chemical subspace.

Jennifer M Elward1, B Christopher Rinderspacher

  • 1Army Research Laboratory, Aberdeen Proving Ground, Aberdeen, MD 21005, USA. berend.c.rinderspacher.civ@mail.mil.

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Summary
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This study compares algorithms for optimizing organic chromophores. A heuristic reordering of search directions best balances hyperpolarizability, absorption limits, and computational cost for electro-optic applications.

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Area of Science:

  • Computational chemistry
  • Materials science
  • Organic electronics

Background:

  • Optimizing chemical compound space is crucial for designing novel materials.
  • Organic chromophores are essential for electro-optic applications.
  • Balancing desired properties with constraints is a key challenge in computational materials design.

Purpose of the Study:

  • To compare various algorithms for optimizing a combinatorial subspace of chemical compound space.
  • To identify the most effective optimization strategy for organic chromophores with specific electro-optic properties.
  • To evaluate algorithms based on maximizing hyperpolarizability while maintaining absorption within 400-700 nm.

Main Methods:

  • Comparison of several optimization algorithms.
  • Application to a test system of organic chromophores.
  • Inclusion of constraints: maximization of hyperpolarizability and absorption wavelength range (400-700 nm).
  • Evaluation of computational cost and feasibility.

Main Results:

  • A heuristic reordering of orthogonal search directions demonstrated the best performance.
  • This method achieved a superior balance between the primary objective (hyperpolarizability), feasibility, and computational expense.
  • The tested algorithms varied significantly in their effectiveness for this specific constrained optimization problem.

Conclusions:

  • Heuristic reordering of orthogonal search directions is a highly effective strategy for optimizing organic chromophores.
  • This approach offers a practical and efficient solution for designing materials with tailored electro-optic properties.
  • The findings provide valuable insights for computational chemists and materials scientists seeking to accelerate materials discovery.