Bulletin of the American Physical Society
APS March Meeting 2022
Volume 67, Number 3
Monday–Friday, March 14–18, 2022; Chicago
Session Y47: Computational Methods for Statistical Mechanics: Advances and Applications IIFocus Recordings Available
|
Hide Abstracts |
Sponsoring Units: DCOMP GSNP Chair: Stefan Boettcher, Emory University Room: McCormick Place W-470B |
Friday, March 18, 2022 8:00AM - 8:36AM |
Y47.00001: TBA Invited Speaker: Naya Banerjee
|
Friday, March 18, 2022 8:36AM - 8:48AM |
Y47.00002: HOOMD-blue v3.0: Creating a modern and extensible API for molecular dynamics and Monte Carlo particle simulations Brandon L Butler, Joshua A Anderson, Sharon C Glotzer HOOMD-blue is a general-purpose toolkit that performs molecular dynamics and Monte Carlo simulations of particles on CPUs and GPUs [1]. In this talk, we describe the design and implementation of the next major release of HOOMD-blue, v3.0. This release includes a new object-oriented Python interface, seamless integration with Python packages like NumPy, increased user extensibility within Python, and a flexible system for accessing and storing computed quantities. For instance, with HOOMD-blue’s v3.0 MoSDeF integration, a simulation’s initial conditions, atom-typing, and force field can be generated through MoSDeF and the simulation run through HOOMD within a single Python script. Version 3.0 changes enable a variety of new simulation methods such as hybrid MC/MD schemes, machine learned force fields, and advanced sampling schemes such as umbrella sampling. Furthermore, custom actions, which allow Python code to be injected into HOOMD’s run loop, streamline the prototyping and developing new simulation techniques and methods for HOOMD users. HOOMD-blue v3.0 is designed with the future of molecular simulations in mind with extensions of all kinds anticipated and facilitated through our Python and C++ APIs. |
Friday, March 18, 2022 8:48AM - 9:00AM |
Y47.00003: Critical and geometric properties of magnetic polymers across the globule-coil transition Kamilla Faizullina, Evgeni Burovski, Ilya Pchelintsev We study a lattice model of a single magnetic polymer chain, where Ising spins are located on the sites of a lattice self-avoiding walk in d=2. We consider the regime where both conformations and magnetic degrees of freedom are dynamic, thus the Ising model is defined on a dynamic lattice, and conformations generate an annealed disorder. Using Monte Carlo simulations, we characterize the globule-coil and ferromagnet-to-paramagnet transitions, which occur simultaneously at a critical value of the spin-spin coupling. We argue that the transition is continuous---in contrast to d=3 where it is first-order. |
Friday, March 18, 2022 9:00AM - 9:12AM |
Y47.00004: A First Look at Structural Properties of Long HP Lattice Protein Sequences Alfred C Farris, David P Landau Despite the apparent simplicity of the HP lattice protein model [1], this class of “simple, exact” models has been extensively studied across disciplines due to either an interest in the principles which govern protein folding [2], the NP-complete computational complexity [3], or both. In this work, we use replica exchange Wang-Landau sampling [4] to study two of the longest HP sequences ever studied (209 and 248 monomers) [5,6]. We extract specific heat curves, report ground state energies, and, for the first time, investigate structural properties of interest for these long sequences. We qualitatively compare the thermodynamics, ground state structures, and structural transitions of these long sequences to each-other and to shorter sequences [7]. |
Friday, March 18, 2022 9:12AM - 9:24AM |
Y47.00005: Many-body theory for the lattice thermal conductivity of crystalline thermoelectrics Axel Hübner, Claudia Draxl, Keith Gilmore, Santiago Rigamonti Thermoelectric materials provide a way to generate electricity in a safe, reliable and sustainable manner. A key property to maximize their efficiency is their lattice thermal conductivity. Modern methods to model this quantity for crystalline solids are either limited by their computational cost (molecular dynamics simulations) or by the quasiparticle approximation used in the Boltzmann transport equation (BTE), which is questionable for bad thermal conductors. We have developed a new methodology for the lattice thermal conductivity using many-body perturbation theory and Hardy's energy-flux operator to overcome these difficulties. It treats the thermal conductivity on a full quantum level, taking into account phonon-phonon correlations beyond the quasiparticle approximation, and is invariant with respect to the gauge choice for the heat flux operator. Importantly, it only requires the same computational cost as the BTE. The method provides a basis to include other effects, such as disorder and electron-phonon interactions and may be applied to the most thermally resistive crystals, such as tin-selenide. We thereby significantly extend the range of materials accessible for lattice thermal conductivity calculations via high-throughput calculations. |
Friday, March 18, 2022 9:24AM - 9:36AM Withdrawn |
Y47.00006: Thermal Conductivity of Polycrystalline Diamond Using Molecular Dynamics Woo Kyun Kim, Chaitanya Kane Because of its high thermal conductivity (~ 2,000 W/m K), diamond is a promising candidate for thermal management applications. In this study, we examine thermal conductivity of polycrystalline diamond using the molecular dynamics method. The interactions between carbon atoms are modeled by the AIREBO potential and the thermal conductivity is computed using both Green-Kubo and the direct methods. Temperature is varied from 300 and 1000 K and the multigrain structure is constructed using Voronoi tessellation. To see the effect of grain size, 1, 2, 5, and 10 grain configurations are chosen. We first compute the thermal conductivity of single crystal diamond as a reference system and then polycrystalline diamond is also tested. The simulation results show that the thermal conductivity drops from 834 W/m K for single crystal to 14.15 W/m K for one grain model. This sharp drop in thermal conductivity is attributed to the grain boundary thermal resistance related to complex lattice dynamics associated with grain boundaries. |
Friday, March 18, 2022 9:36AM - 9:48AM |
Y47.00007: Temperature-dependent Kinetic Pathways of Heterogeneous Ice Nucleation: Competition between Classical and Non-classical Chu Li Ice formation is essential in diverse areas, ranging from climate changing, energy consumption to cell cryopreservation. Compared to ice nucleation in the bulk, the presence of foreign materials in heterogeneous ice nucleation (HIN) complicates the nucleation process, making HIN less comprehended. Here, we employ Markov States models (MSMs) and transition path theory to elucidate the kinetic pathways of HIN simulated by molecular dynamics simulations. Interestingly, our MSMs reveal that the classical one-step and non-classical two-step nucleation pathways can coexist with comparable fluxes at T=230K. We find that the classical one-step pathway with the direct formation of hexagonal ice is promoted by the favorable interactions from the surface. In stark contrast, the non-classical pathway containing intermediate formation of rhombic and hexagonal structures is facilitated by the entropy stabilization of the nucleus via disordered mixing of the two structures. Furthermore, we discover that, at elevated temperatures, the nucleation process shifts towards the classical pathway, mainly because the potential energy difference, which favors the classical pathway, prevails over the configurational entropy compensation. This study provides the underlying kinetics and mechanisms for HIN, shedding light on the possibility to control crystallization. |
Friday, March 18, 2022 9:48AM - 10:00AM |
Y47.00008: Optimization of non-equilibrium self-assembly protocols using Markov State Models Anthony S Trubiano, Michael F Hagan The promise of self-assembly to enable bottom-up formation of novel materials with prescribed |
Friday, March 18, 2022 10:00AM - 10:12AM |
Y47.00009: PySAGES, Enhanced Sampling Molecular Dynamics Simulations on GPUs Pablo Zubieta, Ludwig Schneider, John A Parker, Gustavo R Perez Lemus, Juan De Pablo When performing molecular dynamics simulations, there exists a large gap between the time scales that can be probed computationally to the ones observed in experiments. To tackle this issue two strategies are commonly used: 1) algorithms that explore the simulated configurational space more efficiently; or 2) hardware accelerators such as GPUs. We combine both in PySAGES (Python Suite for Advanced General Ensemble Simulations), which can be hooked to different molecular dynamics (MD) simulation packages, allowing the user to perform enhanced sampling simulations through a uniform interface without sacrificing the efficiency of the underlying MD implementation (at the time of writing we provide support for HOOMD-blue and OpenMM). The library, is a Python implementation of SSAGES with support for GPUs. Having a Python frontend provides the user flexibility and the ability to easily extend it. We will discuss its features, advantages, technical aspects of the implementation, and present some examples and benchmarks. |
Friday, March 18, 2022 10:12AM - 10:24AM |
Y47.00010: VEO, a Vectorized Heuristic to Solve Complex Spin Glass Problems Stefan Boettcher, Mahajabin Rahman We will discuss a new evolutionary search heuristic for NP-hard combinatorial optimization problems. It develops the framework of Extremal Optimization (EO) [1] into a fully vectorized heuristic at a gain in speed of up to ∼N2/100 over EO to solve NP-hard problems such as finding ground-state configurations for many spin glass problems that form complex energy landscapes. To that effect, the random sequential access for updating poorly adapted variables that endows EO with its accuracy has to be significantly re-conceptualized. The resulting implementation of vectorized EO (VEO) deterministically moves an extensive number of those unstable or barely stable variables in each parallel update and only infuses a measured amount of randomness into the process when all such variables are resolved and the system finds itself in a near-optimal configuration. In its focus on updating variables at the edge of stability, VEO (like EO) operates near a critical point of the update dynamics where its high susceptibility entails a broad, pseudo-random exploration of the energy landscape through adaptive avalanches that lead to frequent returns to near-optimal states. Even in its most naive (sequential) implementation, it produces results, e.g., for ground states of the Sherrington-Kirkpatrick spin glass (SK), at much higher efficiency than other methods while producing physically significant results (with <0.1% accuracy) for systems of size N ≈ 104, an order of magnitude improvement. We demonstrate its effectiveness in determining the finite-size corrections to Parisi's replica symmetry breaking calculation for the ground state energy of SK. [1] SB and AG Percus, "Optimization with Extremal Dynamics", PRL86(2001)5211 (https://doi.org/10.1103/PhysRevLett.86.5211). |
Friday, March 18, 2022 10:24AM - 10:36AM |
Y47.00011: Novel criticality in a simple three-dimensional Potts model with next-nearest-neighbor interaction Jun Takahashi We investigate the antiferromagnetic Potts model on the cubic lattice with a next-nearest-neighbor ferromagnetic interaction J'. |
Friday, March 18, 2022 10:36AM - 10:48AM |
Y47.00012: Brittle-to-Ductile Transition of Single-Crystalline Sapphire During Ultra-Precision Machining Woo Kyun Kim, Dalei Xi, Yiyang Du, Aditya Nagaraj, Suk Bum Kwon, Sangkee Min Although sapphire has a wide range of applications due to its superior thermal, electrical, and mechanical properties, the machinability of sapphire is a major challenge due to its inherent brittle nature. Ultra-precision machining has provided a promising solution by enabling ductile-mode cutting, but there remain several problems such as residual stress and surface and subsurface damages after the machining process. In this study, atomic-scale cutting mechanisms of sapphire are investigated using the molecular dynamics (MD) simulation method. The MD simulations are performed on various crystallographic planes and directions of sapphire and the critical depth of cut (CDC) representing the transition from ductile-mode machining to brittle fracture is determined in each case. During the ductile-mode machining, plastic deformation is observed and the corresponding slip systems are identified. When the depth of cut exceeds CDC, fracture is initiated after the small-scale initial slip and twinning occur at the intersection point of different dislocations. The physical origin and mechanisms leading to these different cutting modes are investigated through the analysis of the simulation results. |
Follow Us |
Engage
Become an APS Member |
My APS
Renew Membership |
Information for |
About APSThe American Physical Society (APS) is a non-profit membership organization working to advance the knowledge of physics. |
© 2024 American Physical Society
| All rights reserved | Terms of Use
| Contact Us
Headquarters
1 Physics Ellipse, College Park, MD 20740-3844
(301) 209-3200
Editorial Office
100 Motor Pkwy, Suite 110, Hauppauge, NY 11788
(631) 591-4000
Office of Public Affairs
529 14th St NW, Suite 1050, Washington, D.C. 20045-2001
(202) 662-8700