@article {2101,
	title = {Corrigendum to {\textquotedblleft}Defects and 3D structural inhomogeneity in electron beam additively manufactured Inconel 718{\textquotedblright} [Materials Characterization 143 (2018) 171{\textendash}181]},
	journal = {Materials Characterization},
	volume = {176},
	year = {2021},
	month = {06},
	pages = {111069},
	doi = {10.1016/j.matchar.2021.111069},
	author = {Polonsky, Andrew and Echlin, Mclean and Lenthe, William and Dehoff, Ryan and Kirka, M. and Pollock, Tresa}
}
@article {1526,
	title = {Non-destructive evaluation of 3D microstructure evolution in strontium titanate},
	journal = {Journal of Applied Crystallography},
	volume = {53},
	year = {2020},
	pages = {1{\textendash}11},
	abstract = {<p>
	Nondestructive X-ray diffraction contrast tomography imaging was used to characterize the microstructure evolution in a polycrystalline bulk strontium titanate specimen. Simultaneous acquisition of diffraction and absorption information allows for the reconstruction of shape and orientation of more than 800 grains in the specimen as well as porosity. Three-dimensional microstructure reconstructions of two coarsening states of the same specimen are presented alongside a detailed exploration of the crystallographic, topological and morphological characteristics of the evolving microstructure. The overall analysis of the 3D structure shows a clear signature of the grain boundary anisotropy, which can be correlated to surface energy anisotropy: the grain boundary plane distribution function shows an excess of {\textlangle}100{\textrangle}-oriented interfaces with respect to a random structure. The results are discussed in the context of interface property anisotropy effects.
</p>
},
	keywords = {3d materials, contrast tomography, diffraction, grain growth, microstructure evolution, nondestructive x-ray diffraction contrast, science, strontium titanate, to, tomography imaging was used},
	doi = {10.1107/S160057672000093X},
	author = {Trenkle, Andreas and Syha, Melanie and Rheinheimer, Wolfgang and Callahan, Patrick and Nhuyen, Lily and Ludwig, Wolfgang and Lenthe, William and Echlin, Mclean and Pollock, Tresa and Weygand, Daniel and Hoffmann, Michael and Gumbsch, Peter}
}
@article {1491,
	title = {Microstructure and Property-Based Statistically Equivalent Representative Volume Elements for Polycrystalline Ni-Based Superalloys Containing Annealing Twins},
	journal = {Metallurgical and Materials Transactions A: Physical Metallurgy and Materials Science},
	volume = {49},
	year = {2018},
	pages = {5727{\textendash}5744},
	abstract = {<p>
	This paper has three major objectives related to the development of computational micromechanics models of Ni-based superalloys, containing a large number of annealing twins. The first is the development of a robust methodology for generating 3D statistically equivalent virtual polycrystalline microstructures (3D-SEVPM) of Ni-based superalloys. Starting from electron backscattered diffraction (EBSD) images of sections, the method develops distributions and correlation functions of various morphological and crystallographic parameters. To incorporate twins in the parent grain microstructure, the joint probability of the number of twins and parent grain size, and the conditional probability distributions of twin thickness and twin distance are determined. Subsequently, a method is devised for inserting twins following the distribution functions. The overall methodology is validated by successfully comparing various statistics of the virtual microstructures with 3D EBSD data. The second objective is to establish the microstructure-based statistically equivalent representative volume element or M-SERVE that corresponds to the minimum SERVE size at which the statistics of any morphological or crystallographic feature converge to that of the experimental data. The Kolmogorov\&ndash;Smirnov (KS) test is conducted to assess the convergence of the M-SERVE size. The final objective is to estimate the property-based statistically equivalent RVE or P-SERVE, defined as the smallest SERVE, which should be analyzed to predict effective material properties. The crystal plasticity finite-element model is used to simulate SERVEs, from which the overall material response is computed. Convergence plots of material properties including the yield strength and hardening rate are used to assess the P-SERVE. A smaller P-SERVE compared to the M-SERVE indicates that the characteristic features of twins implemented in determining the M-SERVE are more stringent than those for determining material properties.
</p>
},
	issn = {10735623},
	doi = {10.1007/s11661-018-4858-y},
	url = {https://doi.org/10.1007/s11661-018-4858-y},
	author = {Bagri, Akbar and Weber, George and Stinville, Jean Charles and Lenthe, William and Pollock, Tresa and Woodward, Christopher and Ghosh, Somnath}
}
