BinDev: a Metric of Geometric Accuracy for Plasma-etch 3D Modeling Using Computer Vision : YM: Yield Methodologies

Physics-based semiconductor device and fabrication process modeling provides design and validation solutions for state-of-the-art CMOS and MEMS devices. In this paper, a metric for the geometric differences between two structures visualized by CD-SEM images is defined, and a computer-vision-based algorithm is developed to evaluate the metric. This algorithm is implemented using Python and SEMulator3D ^® , a physics-based process modeling software system for semiconductor and MEMS devices. Computer vision tools, such as filters, thresholding, and morphology operations, are used to extract geometric features from CD-SEM images and pattern matching and symmetric difference are used to compute the metric. Examples of the metric quantifying the geometric similarity between a simulated nanostructure and an experimental CD-SEM image of the fabricated nanostructure are presented. The data consists of eight classes of nanostructures which are defined, fabricated in the cleanroom with 36 combination of layout parameters, and imaged with CD-SEM.