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DL-FIND: An Open-Source Geometry Optimizer for Atomistic Simulations

The Journal of Physical Chemistry A · 2009 · Vol. 113(43) · pp. 11856–11865
Johannes KästnerJoanne M. CarrThomas W. KealWalter ThielA. WanderPaul Sherwood

Abstract

Geometry optimization, including searching for transition states, accounts for most of the CPU time spent in quantum chemistry, computational surface science, and solid-state physics, and also plays an important role in simulations employing classical force fields. We have implemented a geometry optimizer, called DL-FIND, to be included in atomistic simulation codes. It can optimize structures in Cartesian coordinates, redundant internal coordinates, hybrid-delocalized internal coordinates, and also functions of more variables independent of atomic structures. The implementation of the optimization algorithms is independent of the coordinate transformation used. Steepest descent, conjugate gradient, quasi-Newton, and L-BFGS algorithms as well as damped molecular dynamics are available as minimization methods. The partitioned rational function optimization algorithm, a modified version of the dimer method and the nudged elastic band approach provide capabilities for transition-state search. Penalty function, gradient projection, and Lagrange−Newton methods are implemented for conical intersection optimizations. Various stochastic search methods, including a genetic algorithm, are available for global or local minimization and can be run as parallel algorithms. The code is released under the open-source GNU LGPL license. Some selected applications of DL-FIND are surveyed.

Machine Learning in Materials ScienceAdvanced Chemical Physics StudiesProtein Structure and DynamicsConical intersectionEnergy minimizationConjugate gradient methodCartesian coordinate systemComputer scienceIntersection (aeronautics)AlgorithmGradient descentProjection (relational algebra)Geometry

Funding

  • Engineering and Physical Sciences Research Council
Citations
637
FWCI
5.28
field-weighted impact
References
54
Percentile
97%
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Citations per year
References
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