Numerical processing of CNT arrays using 3D image processing of SEM images

• Published in: Robotics and computer-integrated manufacturing Vol. 53; pp. 21 - 27
• Main Authors: Dunn, R.M., Schrlau, M.G.
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.10.2018; Elsevier BV
• Subjects: Arrays; Carbon nanotubes; Computer vision; Data acquisition; Error analysis; Geometry; Human error; Image processing; Nanotechnology; Numerical analysis; Parameters; Scanning electron microscopy; Stereomicroscopy; Studies; Carbon nanotubes; Computer vision; Nanotechnology
• ISSN: 0736-5845; 1879-2537
• DOI: 10.1016/j.rcim.2018.03.002

•A computer vision algorithm to fully analyze the geometry of CNT-arrays.•Uses paired SEM micrographs separated by a tilt to measure tube height.•Computationally inexpensive enough to be run mostly in real-time. This paper outlines an image processing based technique to characterize carbon nanotube (CNT) array devices for enhanced cell transfection. Investigating how manufacturing parameters affects CNT array geometry, and how geometry affects transfection, requires the arrays to be measured. Obtaining a statistically sufficient number of measurements by hand is tedious and subject to human error. An automated system to characterize the arrays facilitates data collection of numerous pore properties. Scanning electron microscopy (SEM) micrographs are pre-processed to identify the location of CNTs which are then measured individually to obtain their characteristics. The data from single pores is aggregated to generate a numerical summary of the array parameters. Stereomicroscopy techniques are used to measure the heights of the CNTs using pairs of tilted images. The overall technique accurately measures the parameters relevant to cell transfection significantly faster than manual measurements while eliminating human error and bias.