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Meeting 2016 TMS Annual Meeting & Exhibition
Symposium ICME Infrastructure Development for Accelerated Materials Design: Data Repositories, Informatics, and Computational Tools
Presentation Title Towards Better Efficiency and Accuracy: Data Mining for Prediction and Optimization in Materials System Design
Author(s) Ankit Agrawal, Alok Choudhary
On-Site Speaker (Planned) Ankit Agrawal
Abstract Scope Deciphering the processing-structure-properties-performance (PSPP) linkages in materials is at the heart of computational materials science. The application of high performance data mining techniques in materials science opens up new avenues for accelerated materials discovery and design, the need for which has also been emphasized by the Materials Genome Initiative. In this talk, I will describe some of the recent works done in our group in collaboration with several materials scientists, employing state-of-the-art data analytics for exploring PSPP linkages, both in terms of forward models (e.g. predicting a material property for a given composition and/or structure) and inverse models (e.g. discovering material compositions and/or structures that possess a desired property). Illustrative works include data-driven analytics on both simulation data like density functional theory (DFT), and experimental data such as processing and composition parameters of steels. Results indicate that such data-driven analytics can significantly accelerate the prediction/optimization process for materials design.
Proceedings Inclusion? Planned: A print-only volume


3D Digital Representations of Knitted Textile Architectures
An ICME Approach to Generation Three Advanced High Strength Steel Development
An ICME Approach to the Investigation of the Relationship between Processing Parameters and Microstructure Development in an Extruded ZE20 Magnesium Alloy
An Integrated Model for Prediction of Yield Stress in Al-7Si-Mg Cast Alloys
Analytics on Large Microstructure Datasets Using 2-pt Statistics
Assessing the State of Manufacturing Process Data and its Potential as a Shared Resource for ICME
Automated Convergence Checks with the Python Based Workbench PyIron
D2C – Converting and Compressing Discrete Dislocation Microstructure Data
Data Curation and Exchange the Easy Way: Modular Data Models and Automated Capture
Data Structures and Algorithms for Thermodynamic and Related Data in the Open Calphad Software System
Development of Common Materials Classification Terminology to Enhance Discoverability, Exchange, and Reuse of Data
Evaluating Image Texture Recognition Algorithms for Generic Microstructure Characterization
Experiences with ICME Information Infrastructures for Applying Materials Models in Sequence to Give Accurate Macroscopic Property Prediction
Genomic Data Infrastructure for Computational Materials Design
Magpie: A Materials-Agnostic Platform for Informatics and Exploration
Materials Data Curation System
Materials Data Management and Chaining of Multiprocess Modeling under the Framework of ICME
Microstructural Modeling of Dynamic Intergranular and Transgranular Fracture Modes in Crystalline Alloys
MIDAS: A Workflow Tool for Improving Materials Strength Modeling
PRISMS: An Integrated Predictive Multi-Scale Capability for the Materials Community
Spectral Database Solutions to Elasto-viscoplasticity within Finite Elements
Statistical Characterization of Microstructure-sensitive Models Applied to Engineering Components
The Materials Data Facility - Data Services to Advance Materials Science Research
Towards an ICME Methodology: Current Activities in Europe
Towards Better Efficiency and Accuracy: Data Mining for Prediction and Optimization in Materials System Design
Web Based Nano-materials Design Platform for Li Ion Battery

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