Bulletin of the American Physical Society
APS March Meeting 2019
Volume 64, Number 2
Monday–Friday, March 4–8, 2019; Boston, Massachusetts
Session E21: Advances in Computational Methods for Statistical Physics and Their Applications IFocus
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Sponsoring Units: DCOMP DCMP GSNP Chair: Ying Wai Li, Oak Ridge National Laboratory Room: BCEC 157B |
Tuesday, March 5, 2019 8:00AM - 8:36AM |
E21.00001: Parallel approaches to long-time atomistic simulations: decomposition, replication, and speculation Invited Speaker: Danny Perez Molecular Dynamics (MD) is a workhorse of computational materials science. Indeed, MD can in principle be used to obtain any thermodynamic or kinetic quantity for a given interatomic potential. This enviable quality however comes at a steep computational price, limiting the system sizes and simulation times that can be achieved in practice. While the size limitation can be efficiently addressed with massively parallel implementations of MD based on spatial decomposition strategies, the same approach cannot extend the timescales much beyond microseconds. This is a significant issue, as this implies that the constant increase in the computing power delivered by leadership-scale machines cannot be leveraged to make long-time predictions. |
Tuesday, March 5, 2019 8:36AM - 8:48AM |
E21.00002: Advanced computational methods for an accurate thermodynamic description of the paramagnetic state of magnetic materials from first principles Davide Gambino, Bjorn Alling In the past years, procedures to calculate from first principles the (Gibbs) free energy of a system with arbitrary accuracy have been established, starting in general from a simplified model and then calculating the full free energy with the use of statistical sampling techniques. These methods have been proven powerful for many materials; however, when it comes to magnetic materials at finite temperature, the system becomes more complex to be treated with ab initio techniques because of the indirect influence of magnetism on several equilibrium properties, besides its explicit contribution to the free energy. |
Tuesday, March 5, 2019 8:48AM - 9:00AM |
E21.00003: Coupled spin dynamics and ab initio molecular dynamics approach for paramagnetic materials Irina Stockem, Anders Bergman, Albert Glensk, Blazej Grabowski, Fritz Körmann, Tilmann Hickel, Jörg Neugebauer, Bjorn Alling Magnetic semiconductors like YMnO3[1] and CrN [2] show an anomalous temperature dependence of the thermal conductivity in their paramagnetic phase: A strong suppression is observed right above the magnetic transition, followed by an almost constant conductivity at higher temperatures. |
Tuesday, March 5, 2019 9:00AM - 9:12AM |
E21.00004: Full spin modeling and efficient mapping of the high dimensional Hamiltonian in Dy2Ti2O7 Anjana Samarakoon, David Tennant, Cristian Batista, Qiang Zhang, Feng Ye, Haidong Zhou, Markus Eisenbach, Kipton Barros, Santiago Grigera, Ying Wai Li, Zhiling Dun Precise modeling of a material is a key to understand its underlying interactions and physics but also revealing the competing phases in the nearby interaction space. Highly frustrated systems are important due to the richness in physics and diversity of phases including spin liquids with exotic topological states they display. Here, we present a machine learning workflow to fit multi-experimental datasets to find an optimal Hamiltonian while undertaking phase classification and extracting information about the topography around the region of interest. Experimental data from a spin-ice material, Dy2Ti2O7 including diffuse neutron scattering, heat capacity, and susceptibility are utilized. This approach is shown to provide the best model in an efficient and effective way but also is powerful at planning the best experimental strategies. |
Tuesday, March 5, 2019 9:12AM - 9:24AM |
E21.00005: Digital Alchemy Applied to Molecular Dynamics James Proctor, Greg Van Anders, Sharon Glotzer Recently, colloidal and nanoparticle synthesis techniques have grown in scope more quickly than the capacity to populate relevant phase diagrams, challenging the predictive ability of computer simulation. Meeting this challenge suggests the development of new techniques that simultaneously explore the dynamics of particles’ canonical degrees of freedom, and particle attributes. Here, we describe a Molecular Dynamics implementation of the “Digital Alchemy” framework. This framework extends statistical ensembles to include variation in “alchemical” degrees of freedom describing particle attributes. We apply alchemical Molecular Dynamics simulations to particles interacting via a Lennard-Jones-Gauss potential, and show that several previously known crystal structures, including a quasicrystal, exhibit stable behavior in this alchemically extended design space, allowing for optimization and exploration. |
Tuesday, March 5, 2019 9:24AM - 9:36AM |
E21.00006: Exploring the Early Stages of Corrosion with ab initio Adaptive Kinetic Monte Carlo Simulations of Non-Equilibrium Oxides Michael Waters, James M Rondinelli The early stages of corrosion in Ni-alloys are dominated by kinetically favorable, non-equilibrium layers comprising normally immiscible oxides. The ionic transport across these highly defective layers mediates their continued growth and the oxidation the substrate alloy. While at longer time scales, the phase segregation of the non-equilibrium layer into thermodynamically stable phases is key to long term passivation of the alloy. In order to simulate the atomistic kinetics on such long-time scales in a natural manner, we employ the state-of-the-art ab initio adaptive kinetic Monte Carlo method. We detail our key findings in regards to the importance of correlation and magnetic order. |
Tuesday, March 5, 2019 9:36AM - 9:48AM |
E21.00007: Removing Lattice Constraints from Lattice Protein Models: A Wang-Landau Study Alfred Farris, Daniel T. Seaton, David P Landau We apply Wang-Landau sampling [1] to the continuum analogue of the hydrophobic-polar (HP) lattice protein model [2] to study the effects of lattice constraints on generic folding behavior in coarse-grained protein models. The continuum version is inspired by the AB polymer model [3], but incorporates potentials chosen specifically to mimic those of the lattice protein case. In this study, we compare and contrast thermodynamics during the folding process of the continuum model to the original HP lattice protein model for sequences mapped from Crambin, a 46 amino acid plant protein. We find that the folding processes for both of these coarse-grained models are quite similar, with major structural transitions occurring at almost the same temperatures. The continuum model hints at a small, additional structural transition not seen in the lattice case; the exact nature of this rearrangement is currently under investigation. |
Tuesday, March 5, 2019 9:48AM - 10:00AM |
E21.00008: Ensemble Monte Carlo Growth simulations of polymers in confined environments Graziano Vernizzi, Trung Nguyen, Henri Orland, Monica Olvera de la Cruz We apply a recent Ensemble Monte Carlo Growth algorithm to sample the microcanonical density of states of polymers in confined geometries. The main advantage of computing the entropy directly, is that it allows to locate and characterize phase transitions accurately, while circumventing problems associated with long time scales. However, when the accessible phase space is restrained, such as in geometrically confined polymers, entropic forces exerted on the confining walls lead to changes in several statistical mechanical properties of the polymers. We test the performance of the microcanonical ensemble Monte Carlo growth algorithm for confined interacting self avoiding walks. We discuss also how to extend the model to include electrostatic interactions. |
Tuesday, March 5, 2019 10:00AM - 10:12AM |
E21.00009: Model Amyloid Protofibrils Simulated with Replica-Exchange Wang-Landau Matthew S. Wilson, Guangjie Shi, David P Landau, Thomas Wuest, Friederike Schmid As neurological diseases associated with toxic peptide aggregates emerge, the research of aggregate and fibril formation has become a prominent, yet extremely challenging problem. The ability to form an amyloid state has been posited as a general feature of peptide systems, and is considered in this study by simulating a collection of coarse-grained, generic model peptides. The H0P model1 adds an additional neutral polarity group to the classic hydrophobic-polar (HP) model2 , and is used for simplicity and efficiency. With the replica-exchange Wang-Landau (REWL) algorithm and an efficient trial move set3, the density of states is determined for multiple interacting model peptides. We observe the formation of fibrillar structures in two continuous transitions that separate three phases: dissolved peptides, disordered oligomers, and crystalline aggregate structures. Additional structural observables are calculated in a post-simulation production run to further study the physical behavior during the observed transitions. |
Tuesday, March 5, 2019 10:12AM - 10:24AM |
E21.00010: Conformational mechanics for polymers doubly-grafted to a homogeneous substrate Shengming Zhang, Michael Bachmann Studies of linear polymer structures with their two ends anchored at a planar substrate can help to provide insights into conformational properties of biologically active systems such as myosin and kinesin. We thoroughly investigated the conformational phases of a coarse-grained flexible homopolymer model with both ends of the chain grafted to a homogeneous attractive substrate by means of parallel tempering computer simulations. For bonded monomers, we employed the FENE potential, whereas the nonbonded interaction was described by the Lennard-Jones potential. The monomer-substrate attraction was modeled using an integrated Lennard-Jones potential. Specific energetic and structural quantities were measured and used as indicator functions for the characterization of the conformational phases in this system. Based on these results, we constructed the temperature versus end-to-end separation pseudo-phase diagram. We identified unique crystalline and icosahedral solid phases in addition to a globular liquid and two geometric gas-like phases. |
Tuesday, March 5, 2019 10:24AM - 10:36AM |
E21.00011: Framework to track Order-Disorder Transitions - From Particles to Block Copolymers Ankita Mukhtyar, Fernando A Escobedo Block copolymers self-assemble into a variety of phases with highly regular patterns, depending on the ordering of molecules. Paramount to understanding and controlling this “order” is to have good “order parameters”, variables used to track changes in the system as it transitions from disorder to order. Molecular dynamics is used to simulate the growth of minimalistic versions of the lamella, cylinder and gyroid phases from an isotropic liquid using a binary nanoparticle mixture model. Based on the correlation of bonding symmetries between a particle and its neighbors, local order parameters are developed and used to track the formation and growth of specific geometric motifs along the transition pathway. They are then modified to study similar transitions in coarse-grained models of polymers and oligomers, namely the assembly of a linear symmetric diblock copolymer into the lamellar, and a branched bolaamphiphile into the single diamond phase. The framework also finds use in the estimation of free-energy barriers for such ordering transitions. These calculations are yet to be reported in literature for such systems and require the use of novel variants of nucleus-size pinning and umbrella sampling techniques. |
Tuesday, March 5, 2019 10:36AM - 10:48AM |
E21.00012: Noise reduction and automated molecule detection in atomistic diffusion calculations of correlated systems Nicola Molinari, Ian Leifer, Yu Xie, Boris Kozinsky When using molecular dynamics to compute diffusion coefficients for correlated systems, the fully correlated analysis of molecular trajectories leads to very noisy estimates because it is based on the center of mass motion rather than motion of individual atoms. We propose a new method that systematically reduces the noise in the diffusion constant calculation. By assuming that the underlying correlation structure of a system is the same for the entire trajectory, we leverage the information learned from the well-converged short-time position-position correlation matrix to reduce the noise at longer times. The proposed method allows to significantly decrease the uncertainty of diffusivity estimates and works for both non-bonded and bonded correlation scenarios. In the latter case we are able to identify automatically the diffusing degrees of freedom of the system, i.e. identify the molecular species. Furthermore, we demonstrate that using our method the estimation of the diffusion constant is never worse than the widely-adopted center-of-mass approach. |
Tuesday, March 5, 2019 10:48AM - 11:00AM |
E21.00013: Scaling relations for the continuum limit from collisions between nanoclusters and rough surfaces Eric Switzer, Aniket Bhattacharya Nanoclusters have wide ranges of applications for their unique size-dependent properties. We report molecular dynamics simulation studies of the coalescence of small clusters with each other and with heterogeneous surfaces, as well as bouncing and fragmentation of clusters. Specifically, we study collisions of dust particles consisting of silica and water molecules and study the aftermath immediately following the collisions. We vary cluster sizes from 10 – 1000 nm containing 1000 – 100,000 particles with an aim to derive scaling relations for the elastic limit so that the extracted elastic parameters for the extrapolated continuum models can be used to study clusters of much larger sizes beyond the scope of simulation studies. |
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