Development of nanoscale magnetic and plasmonic materials for applications such as Heat Assisted Magnetic Recording requires precise control and understanding of the materials’ microstructure. Scanning Electron Microscopy (SEM) has the speed and resolution to characterize grain structure with high throughput, but there is little precedence for imaging sub-50 nm, crystallographically-aligned metal grains in a traditional SEM without specialized detectors or optics. Imaging ungrounded micron-scale metal structures on wafers presents further challenges due to charging. By optimizing imaging parameters for each sample, sub-50 nm and sub-25 nm metal grains were captured. Monte Carlo simulations were used to understand the depth of backscattered electron signal for the stacks of materials and the effect of grain boundary tilt on grain boundary contrast. High-throughput SEM grain imaging as demonstrated in this work yields large materials characterization datasets without expensive detectors or specialized hardware. Translating the qualitative SEM grain images to quantitative characterization requires continued algorithm development, yet there are significant opportunities for automated materials development and structure–property elucidation for SEM grain imaging combined with computer vision. The present and future of magnetic devices requires nanoscale materials control, and high-throughput SEM grain imaging is a promising metrology route for understanding and producing those structures.
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Matthew R. Hauwiller
Charles Mann
P. Mach
AIP Advances
Seagate (United States)
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Hauwiller et al. (Sun,) studied this question.
www.synapsesocial.com/papers/698586ad8f7c464f2300a774 — DOI: https://doi.org/10.1063/9.0001029