A KIM-compliant potfit for fitting sloppy interatomic potentials: application to the EDIP model for silicon

Fitted interatomic potentials are widely used in atomistic simulations thanks to their ability to compute the energy and forces on atoms quickly. However, the simulation results crucially depend on the quality of the potential being used. Force matching is a method aimed at constructing reliable and transferable interatomic potentials by matching the forces computed by the potential as closely as possible, with those obtained from first principles calculations. The potfit program is an implementation of the force-matching method that optimizes the potential parameters using a global minimization algorithm followed by a local minimization polish. We extended potfit in two ways. First, we adapted the code to be compliant with the KIM Application Programming Interface (API) standard (part of the Knowledgebase of Interatomic Models Project). This makes it possible to use potfit to fit many KIM potential models, not just those prebuilt into the potfit code. Second, we incorporated the geodesic Levenberg--Marquardt (LM) minimization algorithm into potfit as a new local minimization algorithm. The extended potfit was tested by generating a training set using the KIM Environment-Dependent Interatomic Potential (EDIP) model for silicon and using potfit to recover the potential parameters from different initial guesses. The results show that EDIP is a "sloppy model" in the sense that its predictions are insensitive to some of its parameters, which makes fitting more difficult. We find that the geodesic LM algorithm is particularly efficient for this case. The extended potfit code is the first step in developing a KIM-based fitting framework for interatomic potentials for bulk and two dimensional materials. The code is available for download via this https URL.

[1]  P. Brommer,et al.  Potfit: effective potentials from ab initio data , 2007, 0704.0185.

[2]  M. J. D. Powell,et al.  A Method for Minimizing a Sum of Squares of Non-Linear Functions Without Calculating Derivatives , 1965, Comput. J..

[3]  James B. Adams,et al.  Interatomic Potentials from First-Principles Calculations: The Force-Matching Method , 1993, cond-mat/9306054.

[4]  Lee-Ping Wang,et al.  Systematic Parametrization of Polarizable Force Fields from Quantum Chemistry Data. , 2013, Journal of chemical theory and computation.

[5]  K. S. Brown,et al.  Bayesian ensemble approach to error estimation of interatomic potentials. , 2004, Physical review letters.

[6]  E. Kaxiras,et al.  INTERATOMIC POTENTIAL FOR SILICON DEFECTS AND DISORDERED PHASES , 1997, cond-mat/9712058.

[7]  Jadwiga Kuta,et al.  ForceFit: A code to fit classical force fields to quantum mechanical potential energy surfaces , 2010, J. Comput. Chem..

[8]  Johannes Roth,et al.  IMD: A Typical Massively Parallel Molecular Dynamics Code for Classical Simulations – Structure, Applications, Latest Developments , 2013 .

[9]  James P. Sethna,et al.  The potential of atomistic simulations and the knowledgebase of interatomic models , 2011 .

[10]  Kaj Madsen,et al.  Methods for Non-Linear Least Squares Problems , 1999 .

[11]  Janet E. Jones On the determination of molecular fields. —II. From the equation of state of a gas , 1924 .

[12]  M. Ortiz,et al.  Quasicontinuum analysis of defects in solids , 1996 .

[13]  Mark K Transtrum,et al.  Geometry of nonlinear least squares with applications to sloppy models and optimization. , 2010, Physical review. E, Statistical, nonlinear, and soft matter physics.

[14]  W Smith,et al.  DL_POLY_2.0: a general-purpose parallel molecular dynamics simulation package. , 1996, Journal of molecular graphics.

[15]  Daw Model of metallic cohesion: The embedded-atom method. , 1989, Physical review. B, Condensed matter.

[16]  Kenneth Levenberg A METHOD FOR THE SOLUTION OF CERTAIN NON – LINEAR PROBLEMS IN LEAST SQUARES , 1944 .

[17]  J. Tersoff,et al.  New empirical model for the structural properties of silicon. , 1986, Physical review letters.

[18]  Michael J. Mehl,et al.  Interatomic potentials for monoatomic metals from experimental data and ab initio calculations , 1999 .

[19]  J. Roth,et al.  Classical interaction potentials for diverse materials from ab initio data: a review of potfit , 2014, 1411.5934.

[20]  Daniel S. Karls Transferability of Empirical Potentials and the Knowledgebase of Interatomic Models (KIM) , 2016 .

[21]  P. Brommer,et al.  Effective potentials for quasicrystals from ab-initio data , 2006, 0704.0163.

[22]  C. G. Broyden A Class of Methods for Solving Nonlinear Simultaneous Equations , 1965 .

[23]  Julian D. Gale,et al.  GULP: A computer program for the symmetry-adapted simulation of solids , 1997 .

[24]  Jörg Stadler,et al.  IMD: A Software Package for Molecular Dynamics Studies on Parallel Computers , 1997 .

[25]  Kaxiras,et al.  Modeling of Covalent Bonding in Solids by Inversion of Cohesive Energy Curves. , 1996, Physical review letters.

[26]  J. Tersoff,et al.  Modeling solid-state chemistry: Interatomic potentials for multicomponent systems. , 1989, Physical review. B, Condensed matter.

[27]  Murray S. Daw,et al.  The embedded-atom method: a review of theory and applications , 1993 .

[28]  Ryan S. Elliott,et al.  Interpolation effects in tabulated interatomic potentials , 2015 .

[29]  Andre K. Geim,et al.  Two-dimensional atomic crystals. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[30]  Susan B. Sinnott,et al.  NSF cyberinfrastructures: A new paradigm for advancing materials simulation , 2013 .

[31]  M. Baskes,et al.  Embedded-atom method: Derivation and application to impurities, surfaces, and other defects in metals , 1984 .

[32]  D. Marquardt An Algorithm for Least-Squares Estimation of Nonlinear Parameters , 1963 .

[33]  E. Kaxiras,et al.  Environment-dependent interatomic potential for bulk silicon , 1997, cond-mat/9704137.

[34]  Janet E. Jones On the Determination of Molecular Fields. I. From the Variation of the Viscosity of a Gas with Temperature , 1924 .

[35]  Mark K Transtrum,et al.  Why are nonlinear fits to data so challenging? , 2009, Physical review letters.

[36]  Michael J. Mehl,et al.  Phase stability in the Fe–Ni system: Investigation by first-principles calculations and atomistic simulations , 2005 .

[37]  K. S. Brown,et al.  Sloppy-model universality class and the Vandermonde matrix. , 2006, Physical review letters.

[38]  P. Morse Diatomic Molecules According to the Wave Mechanics. II. Vibrational Levels , 1929 .

[39]  Ellad B. Tadmor,et al.  Modeling Materials: Continuum, Atomistic and Multiscale Techniques , 2011 .

[40]  Steve Plimpton,et al.  Fast parallel algorithms for short-range molecular dynamics , 1993 .

[41]  Sandro Scandolo,et al.  An ab initio parametrized interatomic force field for silica , 2002 .