Interactive physically-based structural modeling of hydrocarbon systems

  • Authors:
  • Mael Bosson;Sergei Grudinin;Xavier Bouju;Stephane Redon

  • Affiliations:
  • NANO-D - INRIA Grenoble - Rhône-Alpes/CNRS Laboratoire Jean Kuntzmann, 655, avenue de l'Europe Montbonnot, 38334 Saint Ismier Cedex, France;NANO-D - INRIA Grenoble - Rhône-Alpes/CNRS Laboratoire Jean Kuntzmann, 655, avenue de l'Europe Montbonnot, 38334 Saint Ismier Cedex, France;CEMES - CNRS, 29, rue Jeanne-Marvig, BP 94347, 31055 Toulouse Cedex 4, France;NANO-D - INRIA Grenoble - Rhône-Alpes/CNRS Laboratoire Jean Kuntzmann, 655, avenue de l'Europe Montbonnot, 38334 Saint Ismier Cedex, France

  • Venue:
  • Journal of Computational Physics
  • Year:
  • 2012

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Abstract

Hydrocarbon systems have been intensively studied via numerical methods, including electronic structure computations, molecular dynamics and Monte Carlo simulations. Typically, these methods require an initial structural model (atomic positions and types, topology, etc.) that may be produced using scripts and/or modeling tools. For many systems, however, these building methods may be ineffective, as the user may have to specify the positions of numerous atoms while maintaining structural plausibility. In this paper, we present an interactive physically-based modeling tool to construct structural models of hydrocarbon systems. As the user edits the geometry of the system, atomic positions are also influenced by the Brenner potential, a well-known bond-order reactive potential. In order to be able to interactively edit systems containing numerous atoms, we introduce a new adaptive simulation algorithm, as well as a novel algorithm to incrementally update the forces and the total potential energy based on the list of updated relative atomic positions. The computational cost of the adaptive simulation algorithm depends on user-defined error thresholds, and our potential update algorithm depends linearly with the number of updated bonds. This allows us to enable efficient physically-based editing, since the computational cost is decoupled from the number of atoms in the system. We show that our approach may be used to effectively build realistic models of hydrocarbon structures that would be difficult or impossible to produce using other tools.