EZFF: Python Library for Multi-Objective Parameterization and Uncertainty Quantification of Interatomic Forcefields for Molecular Dynamics Institutional Repository Document uri icon

abstract

  • Parameterization of interatomic forcefields is a necessary first step in performing molecular dynamics simulations. This is a non-trivial global optimization problem involving quantification of multiple empirical variables against one or more properties. We present EZFF, a lightweight Python library for parameterization of several types of interatomic forcefields implemented in several molecular dynamics engines against multiple objectives using genetic-algorithm-based global optimization methods. The EZFF scheme provides unique functionality such as the parameterization of hybrid forcefields composed of multiple forcefield interactions as well as built-in quantification of uncertainty in forcefield parameters and can be easily extended to other forcefield functional forms as well as MD engines.

altmetric score

  • 0.5

author list (cited authors)

  • Krishnamoorthy, A., Mishra, A., Kamal, D., Hong, S., Nomura, K., Tiwari, S., ... Vashishta, P.

complete list of authors

  • Krishnamoorthy, Aravind||Mishra, Ankit||Kamal, Deepak||Hong, Sungwook||Nomura, Ken-ichi||Tiwari, Subodh||Nakano, Aiichiro||Kalia, Rajiv||Ramprasad, Rampi||Vashishta, Priya

Book Title

  • arXiv

publication date

  • September 2020