| About this Symposium |
| Meeting |
MS&T24: Materials Science & Technology
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| Symposium
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Additive Manufacturing: Microstructure, Defects, and Properties
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| Sponsorship |
TMS: Additive Manufacturing Committee
TMS: Phase Transformations Committee
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| Organizer(s) |
Nadia Kouraytem, Utah State University
Shenyang Hu, Pacific Northwest National Laboratory
Mohan Sai Kiran Kumar Yadav Nartu, Pacific Northwest National Laboratory (Pnnl)
Srujan Rokkam, Advanced Cooling Technologies, Inc.
Mohsen Asle Zaeem, Colorado School of Mines
Arezoo Emdadi, Missouri University of Science and Technology
Donna P. Guillen, Idaho National Laboratory
Dan Young, Wright State
Iris V. Rivero, University of Florida
Jonathan W. Pegues, Castheon
Eric J. Payton, University of Cincinnati
Ming Chen, Northwestern University
Ashley E. Paz Y Puente, University of Cincinnati
Matthew A. Steiner, University of Cincinnati |
| Scope |
Additive manufacturing (AM) refers to a suite of transformative technologies that enable production of metallic components with complex shape and geometry and facilitate on-demand fabrication of metal parts under austere field conditions. AM processing parameters encapsulate a large set of variables that can directly affect the underlying microstructure, induced defects, and material properties. As a result, it is critical to understand the effect of processing parameters of AM processes on the aforementioned structures and properties.
This symposium invites submissions that focus on the investigation of metal AM processes towards revealing the microstructure, defects, and properties (e.g., modulus of elasticity, tensile strength, elongation, hardness) of the AM materials. Example of topics of interest include but are not limited to the experimental characterization of the microstructure, defects, and properties in metal AM. We encourage abstracts in the broad areas of:
1. Sensing and monitoring of microstructure and/or defect formation
2. Characterization of microstructure and/or defects post facto
3. Evaluation of the variability of mechanical properties (e.g., modulus of elasticity, tensile strength, elongation, hardness) as a function of processing parameters
4. Investigation of the structure-property relationship
5. Modeling and numerical simulation that are validated by experimental measurements |
| Abstracts Due |
05/15/2024 |