@article {1991,
	title = {Scan strategies in EBM-printed IN718 and the physics of bulk 3D microstructure development},
	journal = {Materials Characterization},
	volume = {190},
	year = {2022},
	month = {06},
	pages = {112043},
	doi = {10.1016/j.matchar.2022.112043},
	author = {Polonsky, Andrew and Raghavan, Narendran and Echlin, Mclean and Kirka, M. and Dehoff, Ryan and Pollock, Tresa}
}
@conference {2061,
	title = {3D Characterization of the Columnar-to-Equiaxed Transition in Additively Manufactured Inconel 718.},
	year = {2021},
	month = {09},
	doi = {10.2172/1886524},
	author = {Polonsky, Andrew and Raghavan, Narendran and Echlin, Mclean and Kirka, Michael and Dehoff, Ryan and Pollock, Tresa}
}
@conference {1596,
	title = {3D Characterization of the Columnar-to-Equiaxed Transition in Additively Manufactured Inconel 718},
	booktitle = {Superalloys 2020},
	year = {2020},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	abstract = {<p>
	Additive manufacturing (AM) provides enormous process- ing flexibility, enabling novel part geometries and opti- mized designs. Access to a local heat source further per- mits the potential for local microstructure control on the scale of individual melt pools, which can enable local con- trol of part properties. In order to design tailored process- ing strategies for target microstructures, models predict- ing the columnar-to-equiaxed transition must be extended to the high solidification velocities and complex thermal histories present in AM. Here, we combine 3D charac- terization with advanced modeling techniques to develop a more complete understanding of the solidification pro- cess and evolution of microstructure during electron beam melting (EBM) of Inconel 718. Full calibration of existing microstructure prediction models demonstrates the differ- ences between AM processes and more conventional weld- ing techniques, underlying the need for accurate deter- mination of key parameters that can only be measured directly in 3D. The ability to combine multisensor data in a consistent 3D framework via data fusion algorithms is essential to fully leverage these advanced characteriza- tion approaches. Thermal modeling provides insight on microstructure development within isolated solidification events and demonstrates the role of Marangoni effects on controlling solidification behavior.
</p>
},
	keywords = {Additive manufacturing, Microstructure, Solidification, Tomography},
	isbn = {9783030518349},
	doi = {10.1007/978-3-030-51834-9},
	url = {http://dx.doi.org/10.1007/978-3-030-51834-9_65},
	author = {Polonsky, Andrew T. and Raghavan, Narendran and Echlin, Mclean P. and Kirka, Michael M. and Dehoff, Ryan R. and Pollock, Tresa M.},
	editor = {Tin, Sammy and Hardy, Mark and Clews, Justin and Cormier, Jonathan and Feng, Qiang and Marcin, John and O{\textquoteright}Brien, Chris and Suzuki, Akane}
}
