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ReaxANA: Analysis of Reactive Dynamics Trajectories for Reaction Network Generation.

Hong Zhu1,2, Xin Chen2,3, Jiali Gao1,2,4

  • 1School of Chemical Biology and Biotechnology, Shenzhen Graduate School Peking University, Shenzhen 518055, China.

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We developed ReaxANA, a graph algorithm tool, to denoise reactive molecular dynamics (MD) simulations. This method accurately reconstructs reaction networks and reveals the TNT decomposition pathway via pyrolysis.

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Area of Science:

  • Computational chemistry
  • Chemical kinetics
  • Materials science

Background:

  • Accurate reaction network construction from reactive molecular dynamics (MD) simulations is essential for understanding complex chemical processes like combustion.
  • Existing methods often struggle with noisy trajectory data, hindering the elucidation of macroscopic mechanisms.

Purpose of the Study:

  • To introduce an explicit denoising approach for reactive MD simulations using a graph algorithm.
  • To present ReaxANA, a Python package for extracting reaction mechanisms from MD trajectories.
  • To demonstrate the utility of ReaxANA in analyzing complex systems like TNT explosions.

Main Methods:

  • A graph algorithm-based denoising approach with user-controlled operations (combination, separation, isomerization, node contraction).
  • Implementation in ReaxANA, a parallel Python package operating on atomic position data.
  • Analysis of trinitrotoluene (TNT) explosion system using MD simulations with the ReaxFF force field.

Main Results:

  • ReaxANA effectively removes oscillatory patterns and distinguishes structural isomers in reactive trajectories.
  • The primary decomposition pathway of TNT was identified, involving ortho nitro group pyrolysis and formation of a five-membered ring compound.
  • The software enables comprehensive examination of reaction networks.

Conclusions:

  • ReaxANA provides a robust and versatile tool for analyzing reactive MD simulations.
  • The software facilitates detailed insights into chemical reaction mechanisms, applicable across various simulation platforms.
  • Open-source availability and Docker packaging ensure broad accessibility and cross-platform compatibility.