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Meeting 2018 TMS Annual Meeting & Exhibition
Symposium Computational Materials Discovery and Optimization
Presentation Title Light-metal Complex Hydrides: Computational Structure Prediction and Interaction with Functionalized Nanoporous Hosts
Author(s) Eric Majzoub
On-Site Speaker (Planned) Eric Majzoub
Abstract Scope Crystal structure prediction of complex hydries using simulated annealing Monte Carlo is able to obtain many ground state and polymorph structures when paired with density functional theory. This <I> prototype electrostatic ground states</I> (PEGS) technique was used to search the composition space of possible complex hydrides. PEGS, paired with Wang-Landau MC, was used to investigate the large configuration space of ionic nanoparticle hydrides to predict thermodynamic changes of their de/re-hydriding reactions and to determine nanocluster geometries for higher level first-principles calculations. A brief overview of PEGS and its major results will be presented. Two examples of confinement of hydrides are discussed for carbon-based nanoframeworks both with and without surface functionalization. We explain the wetting behavior of LiBH<SUB>4</SUB> that is melt-infiltrated into a bare nanoporous carbon, and we address Lewis-acid/base complex formation of alane (AlH<SUB>3</SUB>) with pyridinic nitrogen in nitrogen-doped carbon frameworks.
Proceedings Inclusion? Planned: Supplemental Proceedings volume

OTHER PAPERS PLANNED FOR THIS SYMPOSIUM

A Combined Experimental-computational Approach to Determining Nanoscale Structures
A Materials-informatics Approach for Finding New Hard-magnetic Phases
Computational Design of Fatigue-resistant NiTi-based Shape Memory Alloys
Computational Screening of Novel Two-dimensional Topological Insulators and Layer-dependent properties
Data-driven Discovery of Photocathodes for CO2 Reduction
Design Concepts of Optimized MRI Magnet by COMSOL Multiphysics Simulation
Determination of Thermal Transport in Solids and Liquids by Non-equilibrium Molecular Dynamics Simulations
Dual Band Metamaterial Perfect Absorber Based on Mie Resonances
Economic Analysis of National Needs for Technology Infrastructure to Support the Materials Genome Initiative
Fabricating Optimized Crystallographic Textures through Heterogeneous Templated Grain Growth
First-principles Calculations on the Multiferroic Properties of Two-dimensional Oxides
First Principle Prediction of Magnetic Topological Phase in Thin Films of Bi2XY4 (X = Mn, Cr; Y = Se, Te)
High-throughput Investigation of the Electronic Properties of 2D and Bulk Materials in the MaterialsWeb Database
Holistic Computational Structure Screening of More than 12 000 Candidates for Solid Lithium-ion Conductor Materials
Improving the Ductility of Boron Carbide from Computational Design
Learning Grain Boundary Properties from Macroscopic and Microscopic Structural Descriptors
Light-metal Complex Hydrides: Computational Structure Prediction and Interaction with Functionalized Nanoporous Hosts
Machine Learning for Materials
Machine Learning for Prediction of Electronic Structures of Multi-component Alloys
Minimal Addition of Cerium for Stability of Critical Phases in Hard Magnetic AlNiCo Alloys: Combined Machine Learning and CALPHAD
Predicting Ferroelectric Properties from Microstructures with Deep Learning
Quantum-accurate Force Fields from Machine Learning of Large Materials Data
Reentrant Melting of Sodium, Magnesium and Aluminum and Possible Universal Trend
Search for Rare-Earth Free Permanent Magnets in Fe and Co Based Compounds by Adaptive Genetic Algorithm
Software Tools for High-throughput Materials Data Generation and Data Mining
Structure-property Linkages for Porous Membranes Using the Materials Knowledge Systems Framework
Tailoring Properties in Multi-component Alloys through Heuristic Optimization
The Use of Cluster Expansions to Predict the Structure and Properties of Catalysts

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