Bulletin of the American Physical Society
APS March Meeting 2019
Volume 64, Number 2
Monday–Friday, March 4–8, 2019; Boston, Massachusetts
Session S19: Computational Materials Design and Discovery -- Data-Driven Electronic StructureFocus
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Sponsoring Units: DMP DCOMP Chair: Alexander Urban Room: BCEC 156C |
Thursday, March 7, 2019 11:15AM - 11:51AM |
S19.00001: Data-driven design of electronic band structure for materials Invited Speaker: Eric Isaacs Designing a material with a desired electronic band structure is an outstanding challenge in materials physics. In this talk, I will describe an approach using materials database screening with materials attributes based on the constituent elements, nominal electron count, atomic coordination environment, and thermodynamics. Using the over half a million real and hypothetical inorganic crystals of the Open Quantum Materials Database, this approach is applied to two disparate band structure design problems. In the first, we seek a "pudding-mold" band structure containing both flat and dispersive components, which leads to large thermoelectric power factor. One of the identified compounds, BaPdS2, exhibits ultralow lattice thermal conductivity in addition to the pudding-mold band structure, leading to remarkable thermoelectric figure-of-merit approaching 3. In the second, we search for materials with a single correlated d band at low energy, an important yet rare property of the cuprates, to search for possible superconductors and benchmarks for the one-band Hubbard model. Several Cu compounds, including bromide, oxide, selenate, and pyrophosphate chemistries, achieve the desired electronic structure and exhibit properties such as Mott insulating behavior and antiferromagnetism. |
Thursday, March 7, 2019 11:51AM - 12:03PM |
S19.00002: Discovery of Novel Dielectric Materials With Large Energy Bandgaps Using Statistical Optimization Abhijith Gopakumar, Christopher Wolverton We present results from a feedback-based materials design work-flow to find novel materials with optimized dielectric properties. The objective is to improve the performance of electrical devices that depend on charge bearing capacity, which directly depends on dielectric constants and band-gap energies of the compounds. A data-set containing data of dielectric tensors for 1864 materials was extracted from MaterialsProject.org1 to train the statistical deep-learning models. The set of thermodynamically stable materials from OQMD.org2 was used as the search-space to discover novel materials with large values for dielectric constants and bandgap energy. A reliable neural network model was built over the small training data and combined it with statistical optimization strategies. Dielectric properties of predicted materials were computed using Density Functional Perturbation Theory and fed back into subsequent generations of neural network models. Each design cycle in this approach successfully picked up new promising materials from the large search-space, including mixed anion compounds with very large bandgap and dielectric constants - a highly optimized scenario for industrial applications. |
Thursday, March 7, 2019 12:03PM - 12:15PM |
S19.00003: Designing Materials with High Refractive Index and Wide Band Gap: A First-Principles High-Throughput Study Francesco Naccarato, Francesco Ricci, Jin Suntivich, Geoffroy Hautier, Ludger Wirtz, Gian-Marco Rignanese Materials combining both a high refractive index and a wide band gap are of great interest for optoelectronic and sensor applications. However, these two properties are typically described by an inverse correlation with high refractive index appearing in small gap materials and vice-versa. |
Thursday, March 7, 2019 12:15PM - 12:27PM |
S19.00004: Rational Design and Discovery of Novel High
Temperature Superconductors Onyedinachi Ironkwe Rational design of high temperature superconductors, (HTSCs), with predicted stoichiometry and transition temperature, Tc, is a major challenge in superconductivity. We presented in previous APS meetings (2015, 2016, 2017 and 2018), our computational design model called Material Specific Characterization Dataset (MSCD) Framework, and also design algorithms, and generalized periodic system (GPS),for superconductors. Over the past year, we have put to experimental test, our designs of oxide, oxy-sulfide and oxy-chloride systems predicted by MSCD Framework to be HTSCs. At this March 2019 meeting, we present the experimental results of this great challenge and announce the discovery, at ambient pressure of new classes of HTSCs without copper. |
Thursday, March 7, 2019 12:27PM - 1:03PM |
S19.00005: Building and browsing ab initio computational databases in quest of materials with exceptional opto-electronic properties Invited Speaker: Geoffroy Hautier Essential materials properties can now be assessed through ab initio methods. When coupled with the exponential rise in computational power, this predictive power provides an opportunity for large-scale computational searches for new materials. We can now screen thousands of materials by their computed properties even before the experiments. This computational paradigm allows experimentalists to focus on the most promising candidates, and enable researchers to efficiently and rapidly explores new chemical spaces. |
Thursday, March 7, 2019 1:03PM - 1:15PM |
S19.00006: Classification models for high-throughput electronic band structures using feature extraction Bradley Magnetta, Vidvuds Ozolins Applying machine learning techniques to aid materials engineering has become possible due to the existence of large databases of materials data. While models can be built using only scalar data, these databases also provide higher-dimensional data, such as high-throughput electronic band structures, which contain important information for many applications. For instance, the efficiency of thermoelectric materials is known to benefit from certain features in the band structure. We demonstrate how feature extraction techniques can be used to build classification models for band structures and show how these models can be used to aid materials innovation. |
Thursday, March 7, 2019 1:15PM - 1:27PM |
S19.00007: Fully-automated construction of Maximally Localized Wannier Functions: High-Throughput calculations of material properties Valerio Vitale, Giovanni Pizzi, Antimo Marrazzo, Jonathan Yates, Nicola Marzari, Arash A Mostofi Maximally localized Wannier functions (MLWFs) are increasingly used in the computation of advanced properties of materials from first principles and as a localized basis for accurate beyond-DFT methods [1]. |
Thursday, March 7, 2019 1:27PM - 1:39PM |
S19.00008: Universal d=1 flatband generator from compact localized states Wulayimu Maimaiti, Sergej Flach, Alexei Andreanov The band structure of some translationally invariant lattice Hamiltonians contains strictly dispersionless flatbands(FB). These are induced by destructive interference, and typically host compact localized eigenstates (CLS) which occupy a finite number U of unit cells. FBs are important due to macroscopic degeneracy and consequently due to their high sensitivity and strong response to different types of weak perturbations. We use a recently introduced classification of FB networks based on CLS properties, and extend the FB Hamiltonian generator introduced in Phys. Rev. B 95, 115135 (2017) to an arbitrary number ν of bands in the band structure, and arbitrary size U of a CLS. The FB Hamiltonian is a solution to equations that we identify with an inverse eigenvalue problem. These can be solved only numerically in general. By imposing additional constraints, e.g. a chiral symmetry, we are able to find analytical solutions to the inverse eigenvalue problem. |
Thursday, March 7, 2019 1:39PM - 1:51PM |
S19.00009: Coupling of lattice distortions to bands near the Fermi level in ABC compounds from first principles Konrad Genser, Cyrus Dreyer, Jason Kawasaki, Karin Rabe ABC intermetallic compounds exhibit a rich variety of crystal structures and electronic properties. In this work, we use first-principles calculations to elucidate the coupling of lattice distortions to the electronic bands near the Fermi level in a family of hexagonal P6mmc and P63mc ABC compounds, where A is a rare earth, B is a transition metal and C is a main group element. In particular, we have shown that in certain compounds in this family, a polar distortion that buckles the honeycomb layers can open a gap at the Fermi level. In addition, we show that epitaxial strain couples to the bands near the Fermi level directly, as well indirectly through polarization-strain coupling. These results have a number of implications for the targeted design of functional properties in these class of materials, which have been previously proposed as novel candidate ferroelectrics and piezoelectrics. |
Thursday, March 7, 2019 1:51PM - 2:03PM |
S19.00010: Material design of indium-based compounds: possible candidates for charge, valence and bond disproportionation and superconductivity Chang-Jong Kang, Gabriel Kotliar We design and investigate the physical properties of new indium compounds |
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