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A robust and memory-efficient transition state search method for complex energy landscapes.

Samuel J Avis1, Jack R Panter1, Halim Kusumaatmaja1

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We developed a new Binary-Image Transition State Search (BITSS) method to efficiently locate transition states. BITSS is a robust and memory-efficient approach for complex systems, outperforming existing methods.

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Area of Science:

  • Computational Chemistry
  • Materials Science
  • Chemical Engineering

Background:

  • Locating transition states is essential for understanding reaction mechanisms across various scales.
  • Current methods face challenges with high degrees of freedom, adaptive meshing, and complex energy landscapes.

Purpose of the Study:

  • To introduce a novel, robust, and efficient method for transition state identification.
  • To address limitations of existing methods in handling complex systems.

Main Methods:

  • Developed the Binary-Image Transition State Search (BITSS), a double-ended search algorithm.
  • BITSS utilizes two converging states to locate the transition state.
  • Evaluated BITSS on Lennard-Jones clusters, shell buckling, and multiphase phase-field models.

Main Results:

  • BITSS demonstrates speed, flexibility, and memory efficiency.
  • The method shows improved robustness compared to traditional bracketing techniques.
  • Successful application across diverse problem classes highlights its versatility.

Conclusions:

  • BITSS offers a superior approach for transition state identification in complex systems.
  • The method's efficiency and robustness make it suitable for a wide range of phenomena.
  • This work provides a valuable tool for mechanistic investigations in computational science.