Improved conditioning of the Floater--Hormann interpolants

The Floater--Hormann family of rational interpolants do not have spurious poles or unattainable points, are efficient to calculate, and have arbitrarily high approximation orders. One concern when using them is that the amplification of rounding errors increases with approximation order, and can make balancing the interpolation error and rounding error difficult. This article proposes to modify the Floater--Hormann interpolants by including additional local polynomial interpolants at the ends of the interval. This appears to improve the conditioning of the interpolants and allow higher approximation orders to be used in practice.Comment: 13 pages, 4 figures, 1 tabl

Basis functions on the grain boundary space: Theory

With the increasing availability of experimental and computational data concerning the properties and distribution of grain boundaries in polycrystalline materials, there is a corresponding need to efficiently and systematically express functions on the grain boundary space. A grain boundary can be described by the rotations applied to two grains on either side of a fixed boundary plane, suggesting that the grain boundary space is related to the space of rotations. This observation is used to construct an orthornormal function basis, allowing effectively arbitrary functions on the grain boundary space to be written as linear combinations of the basis functions. Moreover, a procedure is developed to construct a smaller set of basis functions consistent with the crystallographic point group symmetries, grain exchange symmetry, and the null boundary singularity. Functions with the corresponding symmetries can be efficiently expressed as linear combinations of the symmetrized basis functions. An example is provided that shows the efficacy of the symmetrization procedure

Classification of atomic environments via the Gromov-Wasserstein distance

Interpreting molecular dynamics simulations usually involves automated classification of local atomic environments to identify regions of interest. Existing approaches are generally limited to a small number of reference structures and only include limited information about the local chemical composition. This work proposes to use a variant of the Gromov-Wasserstein (GW) distance to quantify the difference between a local atomic environment and a set of arbitrary reference environments in a way that is sensitive to atomic displacements, missing atoms, and differences in chemical composition. This involves describing a local atomic environment as a finite metric measure space, which has the additional advantages of not requiring the local environment to be centered on an atom and of not making any assumptions about the material class. Numerical examples illustrate the efficacy and versatility of the algorithm

Continuous and Optimally Complete Description of Chemical Environments Using Spherical Bessel Descriptors

Recently, machine learning potentials have been advanced as candidates to combine the high-accuracy of quantum mechanical simulations with the speed of classical interatomic potentials. A crucial component of a machine learning potential is the description of local atomic environments by some set of descriptors. These should ideally be continuous throughout the specified local atomic environment, twice-differentiable with respect to atomic positions and complete in the sense of containing all possible information about the neighborhood. An updated version of the recently proposed Spherical Bessel descriptors satisfies all three of these properties, and moreover is optimally complete in the sense of encoding all configurational information with the smallest possible number of descriptors. The Smooth Overlap of Atomic Position descriptors that are frequently visited in the literature and the Zernike descriptors that are built upon a similar basis are included into the discussion as being the natural counterparts of the Spherical Bessel descriptors, and shown to be incapable of satisfying the full list of core requirements for an accurate description. Aside being mathematically and physically superior, the Spherical Bessel descriptors have also the advantage of allowing machine learning potentials of comparable accuracy that require roughly an order of magnitude less computation time per evaluation than the Smooth Overlap of Atomic Position descriptors, which appear to be the common choice of descriptors in recent studies.Comment: 15 pages, 5 figures, under review for Journal of Chemical Physic

A Novel Approach to Describe Chemical Environments in High Dimensional Neural Network Potentials

A central concern of molecular dynamics simulations are the potential energy surfaces that govern atomic interactions. These hypersurfaces define the potential energy of the system, and have generally been calculated using either predefined analytical formulas (classical) or quantum mechanical simulations (ab initio). The former can accurately reproduce only a selection of material properties, whereas the latter is restricted to short simulation times and small systems. Machine learning potentials have recently emerged as a third approach to model atomic interactions, and are purported to offer the accuracy of ab initio simulations with the speed of classical potentials. However, the performance of machine learning potentials depends crucially on the description of a local atomic environment. A set of invariant, orthogonal and differentiable descriptors for an atomic environment is proposed, implemented in a neural network potential for solid-state silicon, and tested in molecular dynamics simulations. Neural networks using the proposed descriptors are found to outperform ones using the Behler Parinello and SOAP descriptors currently in the literature.Comment: 23 Pages, 5 figures, 2 tables, journal articl

Analysis of crystallographic texture information by the hyperspherical harmonic expansion

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Materials Science and Engineering, 2009.Cataloged from PDF version of thesis.Includes bibliographical references (p. 223-230).The field of texture analysis is fundamentally concerned with measuring and analyzing the distribution of crystalline orientations in a given polycrystalline material. Traditionally, the orientation distribution function describing crystallographic orientation information is written as a linear combination of the generalized spherical harmonics. Since the use of generalized spherical harmonics requires that orientations be described by sets of Euler angles, the field of texture analysis suffers from the inherent limitations of Euler angles. These include difficulty of presentation and interpretation, discontinuous changes in the description of a changing orientation, and singularities in many equations of Euler angles. An alternative expansion of the orientation distribution function as a linear combination of the hyperspherical harmonics is therefore proposed, with the advantage that this expansion allows rotations to be described by angles that directly relate to the axis and angle of a rotation. Apart from the straightforward and intuitive presentation of orientation statistics that this allows, the utility of the hyperspherical harmonic expansion rests on the fact that the orientation distribution function inherits the useful mathematical properties of the hyperspherical harmonics. The relationship of the hyperspherical harmonics to the three- and four-dimensional rotation groups is investigated, and expressions for the matrix elements of the irreducible representatives of these rotation groups as linear combinations of the hyperspherical harmonics are found.(cont.) These expressions allow an addition formula for the hyperspherical harmonics to be derived, and provide the means to write a simple conversion between the generalized spherical harmonic and hyperspherical harmonic expansions. This allows results derived via the hyperspherical harmonic expansion to be related to the texture analysis literature. Furthermore, a procedure for calculating the symmetrized hyperspherical harmonics consistent with crystal and sample symmetries is indicated, and used to perform the expansion of an orientation distribution function significantly more efficiently. The capability of the hyperspherical harmonic expansion to provide results not traditionally accessible is demonstrated by the generalization of the Mackenzie distribution to arbitrary textures. Finally, further areas where the application of the hyperspherical harmonic expansion is expected to advance the field of texture analysis are discussed.by Jeremy K. Mason.Ph.D

Statistical physics of dislocation nucleation by nanoindentation

Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Physics, 2005.Page 82 blank.Includes bibliographical references (page 79-81).Current understanding of the onset of plasticity during nanoindentation of crystalline materials involves homogenous dislocation nucleation in the crystal underneath the indenter. Through the use of cutting-edge nanoindentation techniques, this study examines the initiation of plastic deformation in single crystal oriented platinum samples. Variations in the temperature and loading rate during indentation reveal temporal and thermal dependencies, and support the stochastic and thermally-activated nature of the initial plastic event. These dependencies of dislocation nucleation are precisely quantified by developing analysis methods based on statistical thermodynamics, and are used to evaluate the probability of various atomistic mechanisms. The results of this procedure implicate a critical activation event occurring in a single atomic volume, with an activation enthalpy of a fraction of an electron volt. These findings strongly indicate that the initiation of plasticity begins with a heterogeneous dislocation nucleation event, in conflict with the current belief, and significantly advance understanding of the onset of plastic deformation during nanoindentation.by Jeremy K. Mason.S.B

Dependence of simulated radiation damage on crystal structure and atomic misfit in metals

This study investigates radiation damage in three metals in the low temperature and high radiant flux regime using molecular dynamics and a Frenkel pair accumulation method to simulate up to $2.0$ displacements per atom. The metals considered include Fe, equiatomic CrCoNi, and a fictitious metal with identical bulk properties to the CrCoNi composed of a single atom type referred to as an A-atom. CrCoNi is found to sustain higher concentrations of dislocations than either the Fe or A-atom systems and more stacking faults than the A-atom system. The results suggest that the concentration of vacancies and interstitials are substantially higher for the CrCoNi than the A-atom system, perhaps reflecting that the recombination radius is smaller in CrCoNi due to the roughened potential energy landscape. A model that partitions the major contributions from defects to the stored energy is described, and serves to highlight a general need for higher fidelity approaches to point defect identification