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research-article

Quantifying Parameter Sensitivity and Uncertainty for Interatomic Potential Design: Application to Saturated Hydrocarbons

[+] Author and Article Information
Mark A Tschopp

Team Leader, ASME Member, U.S. Army Research Laboratory, Aberdeen Proving Ground, MD 21005
mark.a.tschopp.civ@mail.mil

Chris Rinderspacher

Research Chemist, U.S. Army Research Laboratory, Aberdeen Proving Ground, MD 21005
berend.c.rinderspacher.civ@mail.mil

Sasan Nouranian

Assistant Professor, Department of Chemical Engineering, The University of Mississippi, University, Mississippi, 38677
sasan@olemiss.edu

Michael Baskes

Professor, Department of Aerospace Engineering, Mississippi State University, Mississippi State, Mississippi 39762
baskes@bagley.msstate.edu

Steven R. Gwaltney

Professor, Department of Chemistry, Mississippi State University, Mississippi State, Mississippi 39762
sgwaltney@chemistry.msstate.edu

Mark F. Horstemeyer

Professor, Fellow of ASME, Department of Mechanical Engineering, Mississippi State University, Mississippi State, Mississippi 39762
mfhorst@me.msstate.edu

1Corresponding author.

ASME doi:10.1115/1.4037455 History: Received September 01, 2016; Revised January 25, 2017

Abstract

The research objective herein is to understand the relationships between the interatomic potential parameters and properties used in the training and validation of potentials, specifically using a recently-developed modified embedded atom method (MEAM) potential for saturated hydrocarbons (C-H system). This potential was parameterized to a training set that included bond distances, bond angles, and atomization energies at 0 K of a series of alkane structures from methane to n-octane. In this work, the parameters of the MEAM potential were explored through a fractional factorial design and a Latin hypercube design to better understand how individual MEAM parameters affected several properties of molecules (energy, bond distances, bond angles, and dihedral angles) and also to quantify the relationship/correlation between various molecules in terms of these properties. The generalized methodology presented shows quantitative approaches that can be used in selecting the appropriate parameters for the interatomic potential, selecting the bounds for these parameters (for constrained optimization), selecting the responses for the training set, selecting the weights for the various responses in the objective function, and setting up the single/multi-objective optimization process itself. The significance of the approach applied in this study is not only the application to the C-H system, but that the broader framework can be easily applied to any number of systems to understand the significance of parameters, their relationships to properties, and the subsequent steps for designing interatomic potentials under uncertainty.

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