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Meeting MS&T25: Materials Science & Technology
Symposium Materials Informatics for Images and Multi-Dimensional Datasets
Presentation Title Graph-based materials informatics for Fe-based alloy modeling and design
Author(s) Vyacheslav Romanov
On-Site Speaker (Planned) Vyacheslav Romanov
Abstract Scope Understanding of the process‐structure‐property‐performance relationships hidden in materials data can be facilitated by Big Data tools which model the salient features of the process and process-structure relations. Materials informatics (MI) was used in this study to incorporate such knowledge in the domain-specific computational framework. This framework provides not only novel alloy design ideas but also their interpretation via physics and engineering concepts. Fe-based alloy modeling and design was used to demonstrate advantages of the causality-based approach.

OTHER PAPERS PLANNED FOR THIS SYMPOSIUM

3D data pipelines and workflows to mesh experimental and computational results
Application of a Linear Homography Based approach for absolute residual strain extraction from Electron Backscatter Diffraction Patterns
Bidirectional Prediction of Microstructure–Property/Process Relationships in Advanced Structural Materials Using Deep Generative Models
Graph-based materials informatics for Fe-based alloy modeling and design
Harnessing of photodiode signals to predict mechanical properties in laser powder bed fusion additive manufacturing
High Throughput Instrumented Indentation Techniques to Extract Bulk-like Properties of Commercial Metal Alloys
Mapping Microstructure: Manifold Construction and Exploitation for Accelerated Materials Discovery
Microstructure representation with foundational vision models for efficient learning of microstructure--property relationships
Nanocrystalline Films: Imaging, Orientation Mapping, Machine Learning and Data Analytics
Non-destructive 3D characterization of structural failures using X-ray computed tomography
Parametrization of Phases, Symmetries and Defects Through Local Crystallography
Smart E-Waste Sorting: Confidence-Aware Rare Earth and Hazardous Material Mapping via Hyperspectral Imaging

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