Analysis of Actin and Focal Adhesion Organisation in U2OS Cells on Polymer Nanostructures

Background In this work, we explore how U2OS cells are affected by arrays of polymer nanopillars fabricated on flat glass surfaces. We focus on describing changes to the organisation of the actin cytoskeleton and in the location, number and shape of focal adhesions. From our findings we identify that the cells can be categorised into different regimes based on their spreading and adhesion behaviour on nanopillars. A quantitative analysis suggests that cells seeded on dense nanopillar arrays are suspended on top of the pillars with focal adhesions forming closer to the cell periphery compared to flat surfaces or sparse pillar arrays. This change is analogous to similar responses for cells seeded on soft substrates. Results In this work, we explore how U2OS cells are affected by arrays of polymer nanopillars fabricated on flat glass surfaces. We focus on describing changes to the organisation of the actin cytoskeleton and in the location, number and shape of focal adhesions. From our findings we identify that the cells can be categorised into different regimes based on their spreading and adhesion behaviour on nanopillars. A quantitative analysis suggests that cells seeded on dense nanopillar arrays are suspended on top of the pillars with focal adhesions forming closer to the cell periphery compared to flat surfaces or sparse pillar arrays. This change is analogous to similar responses for cells seeded on soft substrates. Conclusion Overall, we show that the combination of high throughput nanofabrication, advanced optical microscopy, molecular biology tools to visualise cellular processes and data analysis can be used to investigate how cells interact with nanostructured surfaces and will in the future help to create culture substrates that induce particular cell function. Graphic Abstract

Spectral Imaging and Computer Vision for High-Throughput Defect Detection and Root-Cause Analysis of Silicon Nanopillar Arrays

Far-field spectral imaging, coupled with computer vision methods, is demonstrated as an effective inspection method for detection, classification, and root-cause analysis of manufacturing defects in large area Si nanopillar arrays. Si nanopillar arrays exhibit a variety of nanophotonic effects, causing them to produce colors and spectral signatures which are highly sensitive to defects, on both the macro- and nanoscales, which can be detected in far-field imaging. Compared with traditional nanometrology approaches like scanning electron microscopy (SEM), atomic force microscopy (AFM), and optical scatterometry, spectral imaging offers much higher throughput due to its large field of view (FOV), micrometer-scale imaging resolution, sensitivity to nm-scale feature geometric variations, and ability to be performed in-line and nondestructively. Thus, spectral imaging is an excellent choice for high-speed defect detection/classification in Si nanopillar arrays and potentially other types of large-area nanostructure arrays (LNAs) fabricated on Si wafers, glass sheets, and roll-to-roll webs. The origins of different types of nano-imprint patterning defects—including particle voids, etch delay, and nonfilling—and the unique ways in which they manifest as optical changes in the completed nanostructure arrays are discussed. With this understanding in mind, computer vision methods are applied to spectral image data to detect and classify various defects in a sample containing wine glass-shaped Si resonator arrays.