Bulletin of the American Physical Society
2020 Annual Meeting of the APS Four Corners Section (Virtual)
Volume 65, Number 16
Friday–Saturday, October 23–24, 2020; Albuquerque, NM (Virtual)
Session B05: Condensed Matter Physics ILive
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Chair: Anita Botana, ASU |
Friday, October 23, 2020 10:30AM - 10:54AM Live |
B05.00001: Low-valence layered nickelates: a cuprate analog for high-temperature superconductivity? Invited Speaker: Antia Botana The physics behind high-temperature superconductivity in cuprates remains a defining problem in Condensed Matter Physics. Among the myriad approaches to addressing this problem has been the study of alternative transition metal oxides with similar structures and electron count that are suggested as proxies for cuprate physics. After 30 years of trying, a non-cuprate compound with a cuprate-like structure that exhibits superconductivity at high temperature has been found: hole-doped NdNiO2. Because this material is a member of a series of reduced layered nickelates, this result suggests the possibility of a new family of unconventional superconductors. By means of first-principles calculations, we have analyzed the similarities and differences between this family of low-valence planar nickelates and cuprates. Even though the nickel oxide materials possess a combination of traits that are widely considered as crucial ingredients for superconductivity in cuprates (a square-planar nature, combined with the appropriate 3d-electron count, and a large orbital polarization) they also exhibit some important differences (a much larger d-p energy splitting, and lack of magnetism in the parent compound). Our results show that low-valence layered nickelates offer a new way of interrogating the cuprate phase diagram and are singularly promising candidates for unconventional superconductivity. [Preview Abstract] |
Friday, October 23, 2020 10:54AM - 11:06AM Live |
B05.00002: Temperature dependence of optical phonon bands in GaP Nuwanjula Samarasingha, Stefan Zollner We explore the effect of temperature on the frequency and linewidth of transverse (TO) and longitudinal (LO) optical phonons in bulk gallium phosphide (GaP) using FTIR ellipsometry from 0.03 to 0.80 eV from 80-720 K. We extract the optical phonon features of GaP by fitting our ellipsometric spectra with the Lowndes--Gervais model, which applies two different broadening parameters to the TO and LO phonons. In GaP, the two-phonon density of state is larger for the decay of TO phonons than for LO phonons. Therefore, we observed a large TO phonon broadening and an asymmetric reststrahlen line shape (compared to the LO phonon). This leads to a negative dielectric constant ($\varepsilon_{\mathrm{2}})$ just above the LO phonon. Two-phonon absorption can be added in the model to avoid this negative $\varepsilon_{\mathrm{2}}$. We find a temperature dependent redshift and broadening of TO and LO phonons with increasing temperature due to anharmonic phonon-phonon decay [1]. These temperature dependent phonon features can be described by three and four phonon decay processes. Also, we investigate the temperature-dependence of the high-frequency dielectric constant. Its variation is explained by thermal expansion and the temperature dependence of the band gap. Reference [1] M. Balkanski, R. F. Walls, and E. Haro, Phys. Rev. B 28, 1928 (1983) [Preview Abstract] |
Friday, October 23, 2020 11:06AM - 11:18AM Live |
B05.00003: Unsupervised machine learning of quantum phase transitions using diffusion maps Alex Lidiak, Zhexuan Gong Experimental quantum simulators have become large and complex enough that discovering new physics from the huge amount of measurement data can be quite challenging, especially when little theoretical understanding of the simulated model is available. Unsupervised machine learning methods are particularly promising in overcoming this challenge. For the specific task of learning quantum phase transitions, unsupervised machine learning methods have primarily been developed for phase transitions characterized by simple order parameters, typically linear in the measured observables. However, such methods often fail for more complicated phase transitions, such as those involving incommensurate phases, valence-bond solids, topological order, and many-body localization. We show that the diffusion map method, which performs nonlinear dimensionality reduction and spectral clustering of the measurement data, has significant potential for learning such complex phase transitions unsupervised. This method may work for measurements of local observables in a single basis and is thus readily applicable to many experimental quantum simulators as a versatile tool for learning various quantum phases and phase transitions. [Preview Abstract] |
Friday, October 23, 2020 11:18AM - 11:30AM Live |
B05.00004: Graph-theoretical analysis of a crystal phase transition James McKenzie, Branton Campbell The group-subgroup relationship between the parent and child phases in a solid-solid phase transition contains valuable information about the types of defects that can arise in the material. In this presentation, we'll explore the role of the symmetry-group of the coset graph of a phase transition in determining defect topology. [Preview Abstract] |
Friday, October 23, 2020 11:30AM - 11:42AM Live |
B05.00005: Exploring the Rich Physics of Triangular Lattice Antiferromagnets with Neutron Scattering Benjamin Frandsen, Raju Baral, Haidong Zhou, Zhiling Dun, Martin Mourigal In geometrically frustrated magnets, the spatial arrangement of magnetic moments on a lattice prevents competing magnetic interactions from being simultaneously satisfied, often leading to exotic magnetic behavior. The canonical example of geometrical frustration consists of antiferromagnetically coupled spins populating a triangular lattice. Here, we explore the compound TmMgGaO$_{\mathrm{4}}$, which hosts Ising-like Tm$^{\mathrm{3+}}$ magnetic moments on a perfect triangular lattice. Using magnetic pair distribution function analysis of neutron scattering data, we study the short-range magnetic correlations present at low temperatures. The results suggest a surprising connection to a topological Kosterlitz-Thouless transition at low temperature, showcasing the rich behavior observed in geometrically frustrated magnets. [Preview Abstract] |
Friday, October 23, 2020 11:42AM - 11:54AM Live |
B05.00006: Visualizing the Short-Range Magnetic Correlations in the Technologically Relevant Semiconductor MnTe Raju Baral, Benjamin Frandsen The antiferromagnetic semiconductor MnTe has recently attracted significant attention as both a high-performance thermoelectric and as a candidate material for spintronics. The magnetic properties of MnTe play a crucial role in both of these possible applications. MnTe has a hexagonal layered structure in which magnetic Mn$^{\mathrm{2+}}$ ions order ferromagnetically within the plane and antiferromagnetically between the planes below T$_{\mathrm{N}} \quad =$ 307 K. Above T$_{\mathrm{N}}$, robust short-range magnetic correlations known as paramagnons survive to high temperature. It has been suggested that these paramagnons are responsible for the high thermoelectric figure of merit zT in Na-doped MnTe at high temperature. Here, we present comprehensive atomic and magnetic pair distribution function (PDF) analysis of neutron total scattering data collected from pure and Na-doped MnTe in the temperature range of 100 K -- 500 K, allowing us to track in detail the evolution of the magnetic correlations from the long-range ordered state at low temperature to the short-range ordered paramagnon state at high temperature. The companion data sets for the pure and doped samples also highlight important differences in the magnetic structure between the two samples. We present real-space magnetic models that reproduce the observed mPDF pattern with quantitative accuracy and discuss the significance of these results in the context of existing work on MnTe. [Preview Abstract] |
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