Bulletin of the American Physical Society
APS March Meeting 2021
Volume 66, Number 1
Monday–Friday, March 15–19, 2021; Virtual; Time Zone: Central Daylight Time, USA
Session C36: Undergraduate Research V: Computational Studies of MaterialsLive Undergrad Friendly
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Sponsoring Units: APS/SPS Chair: Brad Conrad, George Washington University |
Monday, March 15, 2021 3:00PM - 3:12PM Live |
C36.00001: Tilting effect in magneto-absorption of Weyl semimetals Luojia Zhang, Yuxuan Jiang, Dmitry Smirnov, Zhigang Jiang In Weyl semimetals (WSMs), the conduction and valence bands touch at discrete points (Weyl points) in the momentum space with linear dispersed bands around them in all directions. In realistic WSMs, such as NbP, NbAs, TaP, and TaAs, the Weyl bands are tilted, which challenges the application of the previous effective Hamiltonian model in analyzing the magneto-absorption spectra. For instance, tilting is expected to break the axial symmetry of the Weyl band and thus the selection rules for magneto-optical transitions. In this talk, we will examine the tilting effect by constructing a more practical effective Hamiltonian model, incorporating band tilting, asymmetry, and parabolic terms in the band structure. We numerically calculate the Landau levels of WSM in magnetic field in different orientations, from which we obtain the magneto-absorption spectra using Fermi’s golden rule. We extract the tilting effect by comparing our numerical results with the effective Hamiltonian model without tilting. |
Monday, March 15, 2021 3:12PM - 3:24PM Live |
C36.00002: Ambient Conditions Determine the Wettability of Graphene Christina McBean, Priyanka Manchanda, Pratibha Dev The nature of the graphene-water interaction (hydrophobic or hydrophilic) remains a matter of active debate. Earlier experiments studying water-graphene interactions showed graphene to be hydrophobic, in agreement with expectations. More recent works, however, reported that surface-adsorbed hydrophobic contaminants mask graphene’s intrinsic hydrophilicity. In this theoretical work, we use density functional theory to study the effects of “real life” conditions that affect the wettability of graphene. Our calculations reveal that the intrinsic water-graphene interactions have several components, viz., the van der Waals interaction, polarization, and electrostatic interaction. We further show that the presence of ambient gases, defects, and substrates influence these individual components, resulting in the contradictory observations made in experiments. |
Monday, March 15, 2021 3:24PM - 3:36PM Live |
C36.00003: Pressure Effect on Band Inversion in AECd2As2 Jonathan M. DeStefano, Lin-Lin Wang Recent studies have predicted that magnetic EuCd2As2 can host several different topological states depending on its magnetic order1, including a single pair of Weyl points2. Here we report on the bulk properties and band inversion induced by negative pressure in the nonmagnetic analogs AECd2As2 (AE = Ca, Sr, Ba) as studied with density functional theory calculations. Under ambient pressure we find these compounds are narrow band gap semiconductors, in agreement with experimental reports. The application of negative pressure reduces this band gap and causes a band inversion which results in four-fold degenerate Dirac points. The topological nature of these Dirac points is then confirmed by finding the closed Fermi arcs on (10-10) surface. Due to the relatively small negative pressures predicted to reach these Dirac semi-metallic states, we argue that experimental realization can be achievable by the alloying of AECd2As2. |
Monday, March 15, 2021 3:36PM - 3:48PM Live |
C36.00004: Entrainment of Locally-Coupled Josephson Junction SQUID Arrays to an External Magnetic Field Nadav Shaibe, Brad R Trees
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Monday, March 15, 2021 3:48PM - 4:00PM Live |
C36.00005: Numerical Simulation of NV Quantum Spin Dynamics using QuTIP Sarah Edwards, Victoria Norman, Zhipan Wang, Nicholas Curro Nitrogen-vacancy (NV) centers, defects in diamond lattices whose quantum properties can be manipulated using an external magnetic field, are popular in solid-state magnetometry and quantum sensing for their high sensitivity and long coherence times. Typically, NV centers are treated experimentally as two-level systems, considering only the spin = 0 and spin = +1 or -1 cases. However, the full spin-1 multiplet can be exploited to increase sensitivity in AC magnetometry by taking into consideration all three possible orientations of the NV electronic spin, a method referred to double-quantum coherence. This project explores various numerical simulations of magnetic pulse sequences for AC magnetometry via double-quantum coherence using QuTip (qutip.org), a quantum computing package for Python, with the aim of developing techniques to efficiently model double-quantum coherence in NV centers. |
Monday, March 15, 2021 4:00PM - 4:12PM Live |
C36.00006: Distinguishing the optical properties of plasmonics and dielectric nanostructures via machine learning Aniket Pant, Kannatassen Appavoo We demonstrate how machine learning, coupled with dimensionality reduction techniques, allows us to understand and classify the optical response of nanophotonic components with characteristic plasmonic and Mie-dielectric signatures. To reduce the dimensional space of our analytically-calculated spectra of all metallic and dielectric materials, we use principal component analysis (PCA) and t-Distributed Stochastic Neighbor Embeddings (tSNE) as a linear and nonlinear dimensionality reduction technique respectively. Hereafter, by coupling this lower-dimensional space with an XGBoost-based multi-output regressor, we map optical spectra to the linear and nonlinear reduced maps. As experimental validation, we use a 3D electromagnetic full-field simulation solver to generate optical spectra to show that our machine learning technique can identify properties of experimentally-computed nanostructures such as size and intrinsic material properties and which dielectric environment they are in. Our methodology highlights an effective path to discover novel materials for optical sensing. |
Monday, March 15, 2021 4:12PM - 4:24PM Live |
C36.00007: Modeling the Appearance of Viscous Electron Flow in Graphene Using a Scanning Probe Microscope Michael Zirpoli, Sagar Bhandari Graphene is an allotrope of carbon comprised of a single layer of carbon atoms bound in a hexagonal crystalline structure exhibiting two-dimensional characteristics. The effect of these characteristics includes the scattering of electrons that are seen in metals; therefore, graphene has the ability to be much more conductive than commonly used conductors — such as copper. Furthermore, in graphene — at a certain range of temperature and electron density — electrons begin interacting with each other in concert as a viscous fluid. To model and analyze this behavior, Navier-Stokes equations for an incompressible fluid will be implemented. The goal is to construct the best geometry and determine suitable boundary conditions for the walls and circular barrier that show the signature of viscous electron flow. The walls act as the edge of the graphene strip, and the circular barrier acts as the tip perturbation of a scanning probe microscope. By counting the number of particles reaching the drain from the source vs position of the circular barrier, we obtain the map of electron flow through the sample. Mapping the flow of electrons in hydrodynamic regime will shed light on the physics of interacting electrons in graphene and pave way for applications in electronics and optics. |
Monday, March 15, 2021 4:24PM - 4:36PM Live |
C36.00008: Variable-Temperature and Variable-Magnetic Field Relaxation Dynamics of the LIESST State of a
Spin-Crossover Complex Abdullah Durrani, Mark Meisel, Alexandra Barth, Ryan Hadt Due to increased interest in understanding the mechanisms of intersystem crossing and controlling the switching of spin-crossover (SCO) complexes [1], the magnetic field effects on the temperature dependent relaxation rates of the metastable LIESST (light-induced electron spin-state trapping) state were studied in [Fe(ptz)6](BF4)2, where ptz = 1-propyltetrazole, an Fe(II) SCO complex [2] with a |
Monday, March 15, 2021 4:36PM - 4:48PM Live |
C36.00009: Phenomenological modeling of exciton transport in two-dimensional transition metal dichalcogenides Zachary Withers, Dmitri Voronine Excitons dominate the optoelectronic response of two-dimensional (2D) transition metal dichalcogenides (TMDs) because dimensional confinement, dielectric screening, and direct band gaps leads to large exciton binding energies, even at room temperatures. As a result, semiconducting TMDs offers a unique platform for studying exciton dynamics and transport in 2D systems. Classical diffusion-drift models have been commonly used to model exciton transport resulting from varying exciton concentrations and strain engineering. Similarly, rate equations written from level diagrams are commonly used to study exciton dynamics, such as population recombination dynamics, coherent dynamics, and valley polarization dynamics. In this presentation, the aforementioned approaches are combined and the applicability of each model is discussed. In addition, application of the model to strained, junctioned, alloyed systems is discussed. Understanding and optimizing exciton transport and dynamics in 2D TMDs will allow for the creation and optimization of novel devices. |
Monday, March 15, 2021 4:48PM - 5:00PM Live |
C36.00010: Trends in magnetism and magnetic anisotropy of RCo5 materials Justin Edwards, Durga Paudyal The RCo5 family of materials (R = rare earth) are integral to many permanent magnet applications due to their high paramagnetic to ferromagnetic transition (Curie temperature) and potentially high magneto-crystalline anisotropy energy (MAE). These properties make them very attractive for sensitive industrial applications where other permanent magnets fail. We assess all the RCo5 systems within the advanced density function theory (that incorporates onsite electron correlation and spin orbit coupling models) framework by calculating their MAE, magnetic moments, and Curie temperatures. We review experimental anisotropy data and do simple machine learning modeling for first order anisotropy constants at low temperature. We find NdCo5 and SmCo5 with planar (non-useful) and uniaxial (useful) magnetic anisotropy respectively to deviate significantly within the light RCo5 MAE trend. Here we focus on the anomalous behavior of NdCo5 and SmCo5 and find the origin of the deviation stemming from the shape of the 4f charge density. |
Monday, March 15, 2021 5:00PM - 5:12PM Live |
C36.00011: Hexatic glass order of topological defects in the nearly-commensurate charge density phase of 1T-TaS2 Skandaprasad Rao, Michael Altvater, Nikhil Tilak, Choong-Jae Won, Guohong Li, Sang-Wook Cheong, Eva Andrei Tantalum-disulphide (1T-TaS2) exhibits a nearly commensurate charge density wave (NCCDW) phase where competition between commensuration energy and strain causes long-range periodic phase shifts and amplitude modulations of the order parameter. This gives rise to a network of domain walls formed by line defects, fundamental topological excitations of the charge density wave whose intersections can be described as vortices akin to Abrikosov vortices in type II superconductors. According to KTHNY theory, melting of a 2D lattice proceeds via an intermediate hexatic phase characterized by quasi-long range orientational order. We developed software to analyze STM scans of the NCCDW in a 1T-TaS2 sample, allowing us to reveal the nature of the longitudinal and translational correlation functions. We find that the orientational and translational order of the NCCDW vortex lattice is characterized by power law decays with exponents η=0.03(1) and η=0.77(1) respectively. These results suggest that the observed NCCDW vortex lattice forms a rare hexatic glass phase stabilized by interactions with the underlying lattice. |
Monday, March 15, 2021 5:12PM - 5:24PM Live |
C36.00012: Resistance networks with resistances from statistical distributions: exploring how characteristic parameters scale with distance from current input node Sayak Bhattacharjee A random resistance network is a simple yet powerful model to study a multitude of fascinating physical phenomena in condensed matter and statistical physics, owing to the fact that the network models are easily simulated since only scalar quantities are involved. We study a random resistance network constituting of a square lattice wherein the magnitudes of the resistances are obtained from different statistical distributions (all about a fixed mean value), for example, completely random, Gaussian distribution and exponential disorder, as well as resistance fractures. Using these resistance networks, characteristic parameters of the lattice such as equivalent resistance between nodes, optimal current paths, nodal current values etc. are studied. In a particular configuration, where the input current enters the lattice centrally and exits from the four corners of the lattice, the characteristic parameters are studied at large distances for perturbations restricted to varying distances from the central node, to understand the scaling of perturbations with distance from current input node. Computational experiments are carried out and the results are obtained numerically. Analysis carried out aims to explore a broader physical understanding of the results obtained. |
Monday, March 15, 2021 5:24PM - 5:36PM On Demand |
C36.00013: Electronic structure basis of strength and toughness in fluoropolymers Justin Xu, Md Hossain Fluoropolymers (FPs), such as teflon, FEP, PVDF, and ETFE, are a family of fluorocarbon-based plastic resins with different monomeric units of C-F bonds. They have excellent thermoplastic characteristics suitable for industrial applications. While they are engineered by adding or subtracting fluorines with other chemical agents like chlorine and ethylene, a common theoretical platform that can explain the distinctive thermo-mechanical behaviors of different FPs is yet to emerge. From electronic structure calculations using density function theory (DFT) simulations and electron population analyses, we find that electron redistribution is the electronic structure basis for governing mechanical behavior under different deformation conditions. Considering six polymers as example FP variants, we explore their mechanical behaviors by applying uniaxial loading along the C-C chains. Taking atomic variability and arrangement as indicators of chemical heterogeneity, we find that it plays a key role in controlling strength and toughness. Lower chemical heterogeneity and the symmetry of C-H rather than C-F bonds increase strength and toughness of a given polymer. These findings are expected to provide crucial guidance in designing new FPs with unprecedented extreme mechanical properties. |
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