Bulletin of the American Physical Society
Annual Meeting of the APS Four Corners Section
Volume 62, Number 17
Friday–Saturday, October 20–21, 2017; Fort Collins, CO
Session E4: Theoretical and Computational Condensed Matter I |
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Chair: Hua Chen, Colorado State University Room: Lory Student Center 322 |
Friday, October 20, 2017 1:20PM - 1:44PM |
E4.00001: Quantum Confinement Effects in Nano-materials Invited Speaker: Vladimiro Mujica Size-dependent properties and confinement effects are two emerging quantum signatures of nano-systems. They are interrelated and in this talk, I will examine how they can be described in terms of simple quantum models. I will examine how the electronic, optical and magnetic properties of nano-systems and clusters are strongly influenced by the spatial dimensions of the system. As a specific example, we will consider the case of Surface Enhanced Raman Spectroscopy and nano-magnetism. [Preview Abstract] |
Friday, October 20, 2017 1:44PM - 1:56PM |
E4.00002: Non-Hamiltonian Dynamics of Quantized Vortices Scott Strong, Lincoln D. Carr The dynamics of quantized vortices in Bose-Einstein condensates are often modeled by a nonlinear Schr\"odinger equation. In contrast, we show that quantized vortices in fact obey a non-Hamiltonian evolution equation, which enhances dispersion and introduces a gain mechanism. These modifications allow the vortex medium to support helical excitations propagating ahead of a dissipative soliton capable of relaxing localized curvature events into packets of Kelvin waves. Such excitations, absent from previous local induction models, provide a pathway for decay in low-temperature quantum turbulence. [Preview Abstract] |
Friday, October 20, 2017 1:56PM - 2:08PM |
E4.00003: Making materials prediction faster: Choosing integration grids to leverage symmetry Parker Hamilton, Gus Hart, Wiley Morgan, Rodney Forcade In material science, calculations often use complex integrals. These integrals can be expensive and time consuming because the function being integrated is difficult to model. The function does however have symmetry points that can reduce the total number of points needed to perform the integral. It follows that the more symmetries a grid shares with the original function, the easier the integral becomes. We have developed a method to exhaustively enumerate the symmetry preserving grids related to the parent function. This method allows for the generation of a new grid for each parent function that preserves the symmetry of the parent function. [Preview Abstract] |
Friday, October 20, 2017 2:08PM - 2:20PM |
E4.00004: Two-Step Method for Accelerating DFT Calculations using Pre-Generated Charge Densities Hayden Oliver Density Functional Theory packages give us the tools we need to discover new alloys. Unfortunately, the process is very slow. Using a sparse integration grid, we can easily compute the charge density of an alloy, which is then frozen and passed to a much denser grid. By freezing the charge density we hope to accelerate the calculations without sacrificing accuracy by bypassing the more computationally intensive processes of denser grids. We will report on the accuracy/speed trade-offs from using this ``frozen charge" method. [Preview Abstract] |
Friday, October 20, 2017 2:20PM - 2:32PM |
E4.00005: Introducing Correlations into Carrier Transport Simulations of Disordered Materials through Seeded Nucleation: Impact on Density of States, Carrier Mobility, and Carrier Statistics Joshua Brown, Sean Shaheen Disorder in organic semiconductors has made it challenging to achieve performance gains, this is a result of the many competing and often nuanced mechanisms effecting charge transport. In this article, we attempt to illuminate one of these mechanisms in the hopes of aiding experimentalist in exceeding current performance thresholds. Using a heuristic exponential function, energetic correlation has been added to the Gaussian Disorder Model (GDM). The new model is grounded in the concept that energetic correlations can arise in materials without strong dipoles or dopants, but may be a result of an incomplete crystal formation process. The proposed correlation has been used to explain the exponential tail states observed in these materials. It is also better able to capture the carrier mobility field dependence when compared to the GDM. Investigation of simulated current transients shows that the exponential tail states do not necessitate Montrol and Scher fits. Furthermore, we observe that sites located at the boundaries between the seed sites experience the most energetic deviation, are the source of the extended exponential tail states, and are responsible for high charge visitation frequency which may ultimately be associated with material stability. [Preview Abstract] |
Friday, October 20, 2017 2:32PM - 2:44PM |
E4.00006: Machine Learning for Materials Discovery Brayden Bekker, Chandramouli Nyshadham, Gus Hart Advances in fields from engineering to medicine demand the accurate prediction of new materials at an increased rate. The innumerable combination of materials and high computational cost of accurate predictions limits the ability to produce results at the necessary levels. The recently proposed Many Body Tensor Representation (MBTR)(Huo, Haoyan, and Matthias Rupp. ``Unified Representation for Machine Learning of Molecules and Crystals." arXiv preprint arXiv:1704.06439 (2017).) interpolates the materials space to achieve accurate results at a fraction of the computational cost. In this talk, we present the application of MBTR for representing binary/ternary alloys and using machine learning to predict new materials at a faster rate. We show the ability of the MBTR method to meet the increasing demands for fast and accurate materials prediction. [Preview Abstract] |
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