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Meeting 2018 TMS Annual Meeting & Exhibition
Symposium Computational Materials Discovery and Optimization
Presentation Title Opening Electronic Band Gaps in 2D Materials by Deformation Twins
Author(s) Dingyi Sun, David Funes Rojas, Mauricio Ponga
On-Site Speaker (Planned) Dingyi Sun
Abstract Scope In the pursuit to control the electronic properties of 2D materials, a paramount interest has been the manipulation of the band gaps in these materials. Most band gaps in these materials have been primarily dictated by interfacial defects, such as grain boundaries. To introduce systematically-controllable interfaces, we propose the exploitation of twins - a reorientation of the material lattice about a planar discontinuity - in these materials. We use a newly-developed twin framework to kinematically predict novel twin modes in graphene. We then perform a series of atomistic simulations in order to study the energetics of these twin modes, along with their effects on the material band gap and transmission coefficients. Our work opens an avenue to systematically generate novel twin modes in graphene as a means for controlling electronic properties for the advancement of the design of 2D materials, including possible development of phononic metamaterials through twinning.
Proceedings Inclusion? Planned: Supplemental Proceedings volume

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Computational Screening of Novel Two-dimensional Topological Insulators and Layer-dependent properties
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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
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