TRREAT: An algorithm to search a Potential Energy Surface along low curvature pathways. Applications to molecular conformations.
Carlos Campana (Carleton University), Ronald Miller (Carleton University)
From Atomistics to Reality: Spanning Scales in Simulations and Experiments Symposium A
Mon 2:40 - 4:00
CIT 165
A common goal in computational science is to find low energy pathways connecting energy minima in high-dimensional spaces. We introduce the Transition Rapidly-exploring Random Eigenvector Assisted Tree(TRREAT) method as an algorithm to perform searches along low curvature pathways on a potential energy surface (PES). The method combines local curvature information about the PES with an iterative Rapidly-exploring Random Tree algorithm [1,2] that quickly searches high-dimensional spaces for feasible pathways between local minima. We present an in-house TRREAT implementation using Cartesian coordinates that has been coupled to the LAMMPS simulation software [3]. To validate the technique, we apply it to identifying conformational changes of several molecular systems. We analyze the pathway identification problem for alanine dipeptide using the AMBER-03 force field (FF) [4], for cyclohexane using the CHARMM FF [5], and for glycine using a reactive potential based on REAXFF [6]. We show how TRREAT-identified pathways can be used as valuable input guesses for double-ended methods such as the Nudged Elastic Band (NEB) [7] to ascertain Transition state (TS) energies. This method can be utilized to improve/extend the reaction databases that lie at the core of automatic chemical reaction mechanism generator software [8] currently developed to build kinetic models of chemical reactions. [1] J Comput. Chem. 32, 3464,(2011) [2] Proceedings IEEE International Conference on Robotics and Automation, 995-1001, 2000 [3] http://lammps.sandia.gov [4] J. Comput. Chem. 24, 1999,(2003) [5] J. Phys. Chem. B, 102, 3586,(1998) [6] J. Phys. Chem. B, 115, 249,(2011) [7] J. Chem. Phys., 113, 9978,(2000) [8] http://rmg.mit.edu/