Automated scanning routines enable the BND Scanner to map and measure across millimetre areas for sample statistics that are unparalleled. Bespoke algorithms automate the data analysis and provide greater insight and understanding of the whole sample. Statistics are collected quickly and with high confidence leading to strong conclusions and diagnostics across a sample surface.
The image above demonstrates the thresholding process allowing for rapid, large-area analysis. By imaging at discrete points across a sample, surface high-confidence statistics may be collected across the whole surface.
BNDs software thresholds these images allowing these features to be quantified, these features may be pits, bumps, or any feature of a specified size/shape.
CASE STUDY I: PIT COUNTING
The image to the left shows a heat map collected from a polymer surface. Negative features with specified bounding width were identified as pits during thresholding. The heat map shows the spatial distribution of mean pit diameter. Regions of larger diameter pits appear lighter, and regions of smaller diameter pits appear darker.
Selected frames demonstrate the information displayed in the heatmap: a region containing no pits is coloured in black, a region containing many larger ptis appears lighter.
This data was collected over a region of 1 mm.
CASE STUDY II: INCLUSION MAPPING
The image to the right shows a heat map collected from a steel cooling fin. In contrast to case study I, positive features were identified and mapped. These features were carbide precipitates. Carbide precipitates can vary considerably in size and shape leading to differences in macroscale mechanical and corrosion properties.
The image demonstrates how carbide distribution and size can be mapped across a sample of ferritic 9Cr-1Mo steel. The heat map covers an area of 5 mm by 0.5 mm and took 15 minutes to collect.
This research was performed at the University of Bristol and is reported in .
 Liu, C., Heard, P.J., Payton, O.D., Picco, L. and Flewitt, P.E.J., 2019. A comparison of two high spatial resolution imaging techniques for determining carbide precipitate type and size in ferritic 9Cr-1Mo steel. Ultramicroscopy, 205, pp.13-19.