Bulletin of the American Physical Society
APS March Meeting 2023
Volume 68, Number 3
Las Vegas, Nevada (March 5-10)
Virtual (March 20-22); Time Zone: Pacific Time
Session G28: Computational Design, Understanding and Discovery of Novel Materials IIFocus
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Sponsoring Units: DMP Chair: Rodrigo Freitas, MIT; Mauro Del Ben, LBNL Room: Room 220 |
Tuesday, March 7, 2023 11:30AM - 12:06PM |
G28.00001: Elizabeth A. Holm Invited Speaker: Elizabeth Holm
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Tuesday, March 7, 2023 12:06PM - 12:18PM |
G28.00002: Predictive tight-binding model for materials design and understanding Kevin F Garrity, Kamal Choudhary Parameterized tight-binding is a potentially ideal method for large-scale materials design applications, as it combines the speed of |
Tuesday, March 7, 2023 12:18PM - 12:30PM |
G28.00003: The duality between chemical potential diagrams and convex hulls Jiadong Chen, Wenhao Sun Equilibrium phase diagrams are not well-poised to evaluate material stability under dissolution and growth—for example, corrosion and etching; synthesis and deposition; or solid-solid interfacial reactions. These non-equilibrium situations would be better analyzed by phase diagrams that visualize the tendency for a material to gain or lose chemical species, e.g., with a chemical potential axis. Here, we present a generalized phase diagram framework to mix composition and chemical potential axes, providing a new stability representation that applies to these non-equilibrium situations. Our theoretical framework relies on the geometric duality between convex hulls and half-space intersections. It leads to a computational platform that scales efficiently to describe high-dimensional phase boundaries and multi-phase coexistence regions. We discuss how to evaluate and interpret the axes, widths, stability windows, and driving forces on chemical potential diagrams and, importantly, how to connect these to real-world laboratory conditions. Altogether, these mixed composition- and chemical potential diagrams enable materials scientists to evaluate stability in more diverse chemical environments. |
Tuesday, March 7, 2023 12:30PM - 12:42PM |
G28.00004: An all-chemistries comprehensive verification of all-electron and pseudopotential DFT codes via universal common workflows Marnik Bercx, Emanuele Bosoni, Peter Blaha, Jens Bröder, Martin Callsen, Stefaan Cottenier, Augustin Degomme, Espen Flage-Larsen, Marco Fornari, Alberto Garcia, Bonan Zhu, Gian-Marco Rignanese, Georg Kastlunger, Chris J Pickard, Matthias Krack, Daniel Wortmann, Tiziano M Müller, Thomas D Kuhne, Aliaksandr V Yakutovich, Oleg Rubel, Michael Wolloch, Sebastiaan P Huber, Nicola Marzari, Giovanni Pizzi In the past decades many DFT methods and codes have been developed, but only in 2016 their precision was first systematically assessed [1] on elemental compounds. We now define a greatly expanded protocol to test precision and transferability across all chemistries. For each element (Z=1-96) we characterize 10 prototypical compounds (4 unaries and 6 oxides, spanning a wide range of coordination numbers and oxidation states). The first outcome is a reference dataset of 960 equations of state (EOS) cross-checked between two all-electron codes, then used to verify (and improve) ten pseudopotential methods. Such effort is achieved by deploying AiiDA common workflows that provide automatic input parameter selection, identical input/output interface across codes, and full reproducibility. We finally discuss to which extent results can be reused for different goals (e.g., formation energies), and plans to extend common workflow interfaces to more properties (bands, phonons). |
Tuesday, March 7, 2023 12:42PM - 12:54PM |
G28.00005: First principles and data driven simulations of chiral matter Hsuan Ming Yu, Amartya S Banerjee, Shashank Pathrudkar, Susanta Ghosh Chiral matter, i.e., structures with non-superimposable mirror images, offers a great many opportunities for impacting the design of novel electromagnetic, photonic and quantum hardware devices. Chiral matter includes nanostructures with helical and cyclic symmetries and includes quasi-one-dimensional materials such as nanotubes, nanowires, nanoribbons and nanocoils. In this talk, I will outline a set of first principles and data driven approaches for the study of such materials, In particular, I will describe a symmetry adapted real space formulation of Kohn-Sham theory and a machine learning model that is trained on data from such specialized symmetry adapted calculations. I will describe applications of these tools to investigate the electromechanical response of group IV nanotubes under torsional and axial strains, as well as the use of these tools to discover novel phases of chiral matter with strongly correlated electronic states. |
Tuesday, March 7, 2023 12:54PM - 1:06PM |
G28.00006: Direct DFT calculation from nanoscale to bulk stability of icosahedral quasicrystal Woohyeon Baek, Sambit Das, Vikram Gavini, Wenhao Sun The discovery of quasicrystals forced solid-state chemists to revisit traditional assumptions about crystallinity, bonding, stability, and materials formation. Underlying all these questions is a fundamental question: are quasicrystals thermodynamically stable or metastable, but prefer nucleation due to a low surface energy? Density Functional Theory (DFT) is often used to evaluate thermodynamic stability, but quasicrystals are aperiodic and cannot be calculated under periodic boundary conditions. Here, we present a new technique to directly calculate the bulk and surface energies of quasicrystals in DFT. We compute the energies of large quasicrystal nanoparticles, and then fit the bulk and surface energies of the nanoparticles using a Gibbs-Thomson relationship. Using this technique, we evaluate the Tsai-type ScZn and YbCd icosahedral quasicrystals, whose structures have been resolved with atomistic resolution. From the bulk and surface energies, we construct size-dependent phase diagrams, enabling us to determine the bulk and nanoscale (meta)stability of icosahedral quasicrystals. |
Tuesday, March 7, 2023 1:06PM - 1:18PM |
G28.00007: Why are there no metastable structures in binary rocksalts? Matthew C Jankousky, Vladan Stevanovic It is of note that those binary systems that have Rocksalt as their ground state structure appear to only exhibit polymorphism under high pressures or at the nanoscale, and as soon as those conditions are released, the systems will relax back to rocksalt, irrespective of whether the compound is mostly ionic, covalent or metallic. This observation prompted us to do an in-depth theoretical study of the potential energy surface of compounds with the rocksalt ground state. Through ab-initio calculations, we find that ~80 % of all structure-types found for A1B1 compounds in the ICSD database will relax to the rocksalt structure in each of the investigated systems: ionic MgO, covalent PbTe and metallic TaC. In addition, using a previously validated heuristic we examine the remaining prototypes (~20% of them) and their polymorphic transformations into the rocksalt structure, and find that large fraction of them are also expected to transform rapidly into the rocksalt structure. We contrast this with a case with a well-known abundance of metastable allotropes of elemental carbon, or group-IV carbides, in which many low-energy structures exhibit slow transitions into their respective ground states. We therefore propose that the lack of metastable polymorphs in binary rocksalts is mainly a consequence of the rapid nature of the transformation mechanisms between the relevant structure-types and lower energy rocksalt ground state. |
Tuesday, March 7, 2023 1:18PM - 1:30PM |
G28.00008: Simulated Diffusion Spreadability for Characterizing the Structure and Transport Properties of Materials Murray Skolnick, Salvatore Torquato In multiphase heterogeneous media, time-dependent diffusion processes between phases are widespread in physical, chemical, and biological systems. Examples of such media include composites, porous media, and complex fluids. The recently developed diffusion spreadability, ${cal S}(t)$, provides a direct link between time-dependent interphase diffusive transport and the microstructure of two-phase media across length scales [1]; thus making ${cal S}(t)$ a powerful tool for classifying the (non)hyperuniformity of microstructures. In this work, we develop a computationally efficient algorithm for ascertaining ${cal S}(t)$ and its associated entropy production rate directly from digitized representations of microstructures via simulated random walks. We apply our algorithm to a variety of two- and three-dimensional (non)hyperuniform microstructures to assess their non-equilibrium transport properties. Overall, our algorithm has practical use in the discovery and design of materials with desirable time-dependent diffusion properties. |
Tuesday, March 7, 2023 1:30PM - 1:42PM |
G28.00009: Structural optimization in fingerprint space Li Zhu, Shuo Tao, Rishi Rao, Xuecheng Shao Structural optimization has been a crucial component in computational materials research, and structure predictions have relied heavily on this technique in particular. By introducing an extra fingerprint space, we propose a new structural optimization approach that prevents configurations from being stranded in low-symmetry, high-energy conformations. Using this strategy, the chance of achieving low-energy designs has been significantly increased. This performance boost is anticipated to be advantageous for structure search methods that rely on the local optimization of structures. Therefore, the work provides a path toward the objective of predicting the crystal structure of complex systems. |
Tuesday, March 7, 2023 1:42PM - 1:54PM |
G28.00010: Invertible neural networks and more: applications in electronic transport theory Luca Bonaldo, Terry E Stearns, Ilaria Siloi, Nicholas A Mecholsky, Marco Fornari Data-driven and model-driven methods have shown enormous success in both theoretical and applied science. However, when interpreting indirect physical quantities from experimental measurements, the models' validity must be carefully considered. For instance, in electronic structure theory, the values of the effective masses and carrier density are well-defined quantities but are not directly comparable with the measurements. To reconcile the theoretical predictions of a material's effective masses and carrier concentration with experimental analyses, we developed software to automatically link a model band structure to the experimental transport data: electrical conductivity, Seebeck, and Hall coefficients. We first solve very efficiently the direct problem of determining the electronic transport given a multivalley anisotropic parabolic band structure, then we tackle the inverse problem of reconstructing candidates' band structures from the experimental results. The software uses four techniques to tame the inverse problem: reverse Monte Carlo algorithm, invertible neural network, partially observable Markov decision processes, and a Bayesian method. |
Tuesday, March 7, 2023 1:54PM - 2:06PM |
G28.00011: Why does silicon have an indirect band gap? Emily Oliphant, Madison Brod, Jeff Snyder, Emmanouil Kioupakis, Wenhao Sun First-principles methods are routinely used to predict electronic band structures, but they rarely deliver intuition on the crystal chemistry origin of major qualitative band structure features like band gap magnitude, location of band extrema, effective masses, etc. However, all real-space bonding interactions can be derived from a tight-binding decomposition of the electronic structure, which explains the chemical and orbital origin of band structure features. Here, we examine the duality between real-space bonding interactions and reciprocal-space electronic structure by relating the chemical bond-type at distinct k-points; as well as by determining the reciprocal space band dispersion for distinct orbital interactions. Applying this to silicon, we present new mechanistic insights on how multiple orbital interactions combine to form the low-symmetry conduction band minimum along the Γ-X line. Specifically, we find that the linear nature of the 1st nearest-neighbor interactions combines with the cosine nature of the 2nd nearest-neighbor px–px bonding to form a minimum near X. Applying this method to understand band features can lead to the conceptual design of materials with superlative optoelectronic and magnetic properties. |
Tuesday, March 7, 2023 2:06PM - 2:18PM |
G28.00012: How Global is the Global Instability Index? Kyle D Miller, James M Rondinelli The global instability index (GII) is an inexpensive bond valence theory-based metric originally designed to evaluate the total bond strain in a crystal. Although prior studies have proven GII is an effective predictor of structural distortions and decomposition energy when applied to small data sets, the wider use of GII as a global indicator of structural stability has yet to be evaluated. To that end, we compute GII for thousands of compounds in inorganic structure databases and partition compounds by chemical interactions underlying their stability to understand GII. We find that structural prototype, chemistry, and electronic character significantly impact the GII of a crystal, contraindicating its use as a general measure of the feasibility of a structure. |
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