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Meeting 2018 TMS Annual Meeting & Exhibition
Symposium Computational Materials Discovery and Optimization
Presentation Title Economic Analysis of National Needs for Technology Infrastructure to Support the Materials Genome Initiative
Author(s) Troy Scott, Alan O'Connor, Gregory Tassey, Amanda Walsh, Benjamin Anderson
On-Site Speaker (Planned) Troy Scott
Abstract Scope A study, recently completed by RTI International on behalf of the National Institute of Standards and Technology (NIST), analyzes standards, measurement, and general purpose technology needs that inhibit efficient development and deployment of advanced materials by U.S. manufacturers. The study, based on in-depth interviews with industry experts, identifies industry needs related to materials innovation infrastructure, elucidates barriers to meeting these needs, estimates the economic impact of overcoming these barriers, and reviews and prioritizes public policy and investment options. Highlighted areas of industry need include access to high-quality scientific and engineering data, efficient means of sharing materials information in collaborative networks, platform process technologies for computational materials design, robust model-based alternatives to expensive physical testing, basis for trust and acceptance of computational models and objective decision making regarding reliance on computational methods at the business level.
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 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
L-27: Computational Design of Fatigue-resistant NiTi-based Shape Memory Alloys
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
Molecular Crystal Structure Prediction with Gator and Genarris
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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