Bulletin of the American Physical Society
APS March Meeting 2014
Volume 59, Number 1
Monday–Friday, March 3–7, 2014; Denver, Colorado
Session D12: Invited Session: Materials Genome: Theory-Led Accelerated Materials Discovery |
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Sponsoring Units: DMP Chair: Darrell Schlom, Cornell University Room: 205 |
Monday, March 3, 2014 2:30PM - 3:06PM |
D12.00001: Oxide Materials Invited Speaker: Mark Asta |
Monday, March 3, 2014 3:06PM - 3:42PM |
D12.00002: Using your own computer to search for novel materials (with a little help from the aflowlib.org consortium online library) Invited Speaker: Stefano Curtarolo In this presentation, we show how to use on-line resources to search for novel thermoelectrics, topological-insulators, magnets, and binary/ternary phase diagrams.\\[4pt] In collaboration with Ohad Levy, Materials Science, Duke University; Marco Buongiorno Nardelli, University of North Texas; and Natalio Mingo, CEA, Grenoble. [Preview Abstract] |
Monday, March 3, 2014 3:42PM - 4:18PM |
D12.00003: Computational Discovery and Design of Two-Dimensional Materials for Energy Technologies Invited Speaker: Richard G. Hennig Our research focuses on the development of new methods and algorithms to discover materials and to describe realistic heterogeneous interfaces and the application of these methods to the discovery and design of novel two-dimensional materials for application in energy technologies and electronic devices. In this talk, I will present our data-mining approach to identify novel two-dimensional materials with low formation energies. We identify several 2D materials in the group-III monochalcogenides and the group of transition metal dichalcogenides that are suitable for photocatalytic water splitting. We show that these 2D materials in contrast to their 3D counterparts have appropriate bad gaps and alignments with the redox potentials of water, and exhibit high solvation energies, indicating their stability in aqueous environment. We show that strain can be used to tune the electronic and optical properties of these materials. Our results provide guidance for experimental synthesis efforts and future searches of materials suitable for applications in energy technologies.\\[4pt] In collaboration with Houlong L. Zhuang, Arunima K. Singh, Michael N. Blonsky, Department of Materials Science and Engineering, Cornell University, Ithaca, New York 14853, USA; and Michelle D. Johannes, Department of Materials Science and Engineering, Cornell University and Naval Research Laboratory, 4555 Overlook Avenue, SW, Washington, District of Columbia 20375, USA. [Preview Abstract] |
Monday, March 3, 2014 4:18PM - 4:54PM |
D12.00004: Random search - a tool for exploring dense matter Invited Speaker: Chris Pickard There has been great progress in the prediction of structure from first principles - thanks to the combination of stochastic search algorithms with reliable density functional based evaluations of the energy landscape. My approach - Ab Initio Random Structure Searching (AIRSS) [1,2] is particularly simple and powerful. In its most straightforward implementation, a lack of bias makes it suitable for theoretical explorations which can lead to new and unexpected phenomena. I have uncovered ionic phases of ammonia [3], and structural richness at terapascal pressures in aluminium [4]. An emphasis has been placed on the hunt for novel physics, illustrated by the discovery of a new route to bulk magnetism in the elements [5] and the decomposition of water under terapascal conditions [6]. The imposition of geometrical constraints permits the directed search for the ground state structure of complex compounds - I will discuss the application of AIRSS to the computational discovery of new materials. \\[4pt] [1] C.J. Pickard and R.J. Needs, Phys. Rev. Lett. 2006, 97, 45504.\\[0pt] [2] C.J. Pickard and R.J. Needs, J. Phys.: Condens. Matter Topical Review 2011, 23, 053201.\\[0pt] [3] C.J. Pickard and R.J. Needs, Nature Materials 2008, 7, 775-779.\\[0pt] [4] C.J. Pickard and R.J. Needs, Nature Materials 2010, 9, 624-627.\\[0pt] [5] C.J. Pickard and R.J. Needs, Phys. Rev. Lett. 2011, 107, 087201.\\[0pt] [6] C.J. Pickard, Miguel Martinez-Canales, and R.J. Needs, Phys. Rev. Lett. 110, 245701 (2013) [Preview Abstract] |
Monday, March 3, 2014 4:54PM - 5:30PM |
D12.00005: The ``Missing Compounds'' affair in functionality-driven material discovery Invited Speaker: Alex Zunger In the paradigm of ``data-driven discovery,'' underlying one of the leading streams of the Material Genome Initiative (MGI), one attempts to compute high-throughput style as many of the properties of as many of the N (about 10**5- 10**6) compounds listed in databases of previously known compounds. One then inspects the ensuing Big Data, searching for useful trends. The alternative and complimentary paradigm of ``functionality-directed search and optimization'' used here, searches instead for the n much smaller than N configurations and compositions that have the desired value of the target functionality. Examples include the use of genetic and other search methods that optimize the structure or identity of atoms on lattice sites, using atomistic electronic structure (such as first-principles) approaches in search of a given electronic property. This addresses a few of the bottlenecks that have faced the alternative, data-driven/high throughput/Big Data philosophy: (i) When the configuration space is theoretically of infinite size, building a complete data base as in data-driven discovery is impossible, yet searching for the optimum functionality, is still a well-posed problem. (ii) The configuration space that we explore might include artificially grown, kinetically stabilized systems (such as 2D layer stacks; superlattices; colloidal nanostructures; Fullerenes) that are not listed in compound databases (used by data-driven approaches), (iii) a large fraction of chemically plausible compounds have not been experimentally synthesized, so in the data-driven approach these are often skipped. In our approach we search explicitly for such ``Missing Compounds''. It is likely that many interesting material properties will be found in cases (i)-(iii) that elude high throughput searches based on databases encapsulating existing knowledge. I will illustrate (a) Functionality-driven discovery of topological insulators and valley-split quantum-computer semiconductors, as well as (b) Use of ``first principles thermodynamics'' to discern which of the previously ``missing compounds'' should, in fact exist and in which structure. Synthesis efforts by Poeppelmeier group at NU realized 20 never-before-made half-Heusler compounds out of the 20 predicted ones, in our predicted space groups. This type of theory-led experimental search of designed materials with target functionalities may shorten the current process of discovery of interesting functional materials. [Preview Abstract] |
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