Theoretische Chemie, Ruhr-Universität Bochum, Germany,
Homepage of the Behler group

The RuNNer Code

Jörg Behler

Lehrstuhl für Theoretische Chemie, Ruhr-Universität Bochum

In order to develop Neural Network potential-energy surfaces for a variety of system, we have developed our own NN code called RuNNer. The code is currently still under development and not yet publicly available.

RuNNer has the following features:
  1. unlimited number of degrees of freedom (atoms)
  2. training data can be obtained from arbitrary electronic structure methods and codes
  3. training using energies and forces
  4. periodic and non-periodic system
  5. several types of symmetry functions are available
  6. several types of activation functions are available
  7. arbitrary topology of the atomic neural networks
  8. provides energies and analytic derivatives (forces and stress tensor)

The methodology of RuNNer is published in the following papers:

J. Behler, and M. Parrinello, Phys. Rev. Lett. 98, 146401 (2007).
J. Behler, R. Martonak, D. Donadio, and M. Parrinello, phys. stat. sol. (b) 245, 2618 (2008).
J. Behler, J. Chem. Phys. 134, 074106 (2011).

More details will follow soon. If you are interested in learning more about RuNNer, please feel free to contact us.

Link to the internal RuNNer page

Homepage of the Behler group
Theoretische Chemie, Ruhr-Universität Bochum, Germany,

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