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 |