@article {1431,
	title = {Advanced detector signal acquisition and electron beam scanning for high resolution SEM imaging},
	journal = {Ultramicroscopy},
	volume = {195},
	year = {2018},
	pages = {93{\textendash}100},
	abstract = {<p>
	The advancement of materials science at the mesoscale requires improvements in both sampling volumes/areas and spatial resolution in order to make statistically significant measurements of microstructures that influence higher-order material properties, such as fatigue and fracture. Therefore, SEM-based techniques have become desirable due to improvements in imaging resolution, large sample handling capability, and flexibility for in-situ instrumentation. By using fast sampling of SEM electron detector signals, intrinsic beam scanning defects have been identified that are related to the response time of the SEM electron beam deflectors and electron detectors. Mitigation of these beam scanning defects using detector sampling approaches and an adaptive model for settling time is shown to produce higher resolution SEM images, at faster image acquisition times, with a means to quantify the different response functions for various beam deflectors and detectors including those for electrons and ions.
</p>
},
	keywords = {High resolution digital image correlation, Image processing, Imaging defects, Scan generator, Scanning electron microscopy, SEM},
	issn = {18792723},
	doi = {10.1016/j.ultramic.2018.08.025},
	url = {https://doi.org/10.1016/j.ultramic.2018.08.025},
	author = {Lenthe, William C. and Stinville, Jean Charles and Echlin, Mclean P. and Chen, Zhe and Daly, Samantha and Pollock, Tresa M.}
}
@article {1471,
	title = {Application of chord length distributions and principal component analysis for quantification and representation of diverse polycrystalline microstructures},
	journal = {Materials Characterization},
	volume = {145},
	year = {2018},
	pages = {671{\textendash}685},
	abstract = {<p>
	Quantification of mesoscale microstructures of polycrystalline materials is important for a range of practical tasks of materials design and development. The current protocols of quantifying grain size and morphology often rely on microstructure metrics (e.g., mean grain diameter) that overlook important details of the mesostructure. In this work, we present a quantification framework based on directionally resolved chord length distribution and principal component analysis as a means of extracting additional information from 2-D microstructural maps. Towards this end, we first present in detail a method for calculating chord length distribution based on boundary segments available in modern digital datasets (e.g., from microscopy post-processing) and their low-rank representations by principal component analysis. The utility of the proposed framework for capturing grain size, morphology, and their anisotropy for efficient visualization, representation, and specification of polycrystalline microstructures is then demonstrated in case studies on datasets from synthetic generation, experiments (on Ni-base superalloys), and simulations (on steel during recrystallization).
</p>
},
	keywords = {Chord length distribution, EBSD, Grain size, Microstructure, Principal component analysis},
	issn = {10445803},
	doi = {10.1016/j.matchar.2018.09.020},
	url = {https://doi.org/10.1016/j.matchar.2018.09.020},
	author = {Latypov, Marat I. and K{\"u}hbach, Markus and Beyerlein, Irene J. and Stinville, Jean Charles and Toth, Laszlo S. and Pollock, Tresa M. and Kalidindi, Surya R.}
}
