GROW: a gradient-based optimization workflow for the automated development of molecular. The concept, issues of implementation and file formats of the GRadient-based Optimization Workflow for the Automated Development of Molecular Models ‘GROW’ (version 1.0) software tool are described. It enables users to perform automated optimizations of force field parameters for atomistic molecular simulations by an iterative, gradient-based optimization workflow. The modularly constructed tool consists of a main control script, specific implementations and secondary control scripts for each numerical algorithm, as well as analysis scripts. Taken together, this machinery is able to automatically optimize force fields and it is extensible by developers with regard to further optimization algorithms and simulation tools. Results on nitrogen are briefly reported as a proof of concept.
Keywords for this software
References in zbMATH (referenced in 3 articles )
Showing results 1 to 3 of 3.
- Griebel, Michael (ed.); Schüller, Anton (ed.); Schweitzer, Marc Alexander (ed.): Scientific computing and algorithms in industrial simulations. Projects and products of Fraunhofer SCAI (2017)
- Krämer, Andreas; Hülsmann, Marco; Köddermann, Thorsten; Reith, Dirk: Automated parameterization of intermolecular pair potentials using global optimization techniques (2014)
- Hülsmann, Marco; Köddermann, Thorsten; Vrabec, Jadran; Reith, Dirk: \textttGROW: a gradient-based optimization workflow for the automated development of molecular models (2010)