Classical interaction potentials for diverse materials fromab initiodata: a review ofpotfit

Abstract

Force matching is an established technique to generate effective potentials for molecular dynamics simulations from first-principles data. This method has been implemented in the open source code potfit. Here, we present a review of the method and describe the main features of the code. Particular emphasis is placed on the features added since the initial release: interactions represented by analytical functions, differential evolution as optimization method, and a greatly extended set of interaction models. Beyond the initially present pair and embedded-atom method potentials, potfit can now also optimize angular dependent potentials, charge and dipolar interactions, and electron-temperature-dependent potentials. We demonstrate the functionality of these interaction models using three example systems: phonons in type I clathrates, fracture of α-alumina, and laser-irradiated silicon.

A minimal Tersoff potential for diamond silicon with improved descriptions of elastic and phonon transport properties

“…where f i (n) and f DFT i (n) are the force on the i-th atom in the n-th structure calculated from the empirical potential and DFT, respectively. The above fitness function is similar to those used in the potfit [49] and POPS [47] packages.…”

Design, Parameterization, and Implementation of Atomic Force Fields for Adsorption in Nanoporous Materials

“…Potfit (https://github.com/potfit) is a free implementation of the forcematching algorithm to generate effective potentials from ab initio reference data. [328] DFTFIT (https://github.com/costrouc/dftfit) is a python code that uses ab initio data from DFT calculations such as VASP, Quantum Espresso, and Siesta to develop molecular dynamic potentials. DFTFIT uses the least square method to fit the stresses, total energy, and forces of a given set of configurations.…”

The role of ceramic and glass science research in meeting societal challenges: Report from an NSF‐sponsored workshop

“…DFT can be used to generate quantum‐accurate potentials for atomic scale simulations, to model interfacial structure, energies, and the stability of nanoscale features. New automated techniques can generate accurate potentials when combined with DFT methods, and inform the design of the complex interfaces that are anticipated with the advanced architectures of heterogeneous materials . They can also provide mechanistic understanding of materials processes such as diffusion, interface mobilities, and phase transitions.…”

“…New automated techniques can generate accurate potentials when combined with DFT methods, and inform the design of the complex interfaces that are anticipated with the advanced architectures of heterogeneous materials. [42][43][44] They can also provide mechanistic understanding of materials processes such as diffusion, interface mobilities, and phase transitions. Mesoscale modeling, predominantly phase field 45 and Potts kinetic Monte Carlo models, 46 can treat microstructure and its evolution at processing temperatures of interest under different energy fields when applicable.…”