Generation of large field SEM image by panorama composition technology for nano-order measurement
| Autor: | Yutaka Hojyo, Atsushi Miyamoto |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Observational error
Panorama Basis (linear algebra) Semiconductor device fabrication business.industry Computer science Applied Mathematics 02 engineering and technology 021001 nanoscience & nanotechnology 01 natural sciences Connection (mathematics) Image (mathematics) 010309 optics Optics 0103 physical sciences Line (geometry) Computer vision Artificial intelligence Photomask 0210 nano-technology business Instrumentation Engineering (miscellaneous) |
| Zdroj: | Measurement Science and Technology. 27:025407 |
| ISSN: | 1361-6501 0957-0233 |
| DOI: | 10.1088/0957-0233/27/2/025407 |
| Popis: | Semiconductor manufacturing has a pressing need for a method to accurately evaluate the global shape deformation of a photomask pattern. We thus propose a novel composition technique for a large field panorama image of scanning electron microscopy (SEM). The proposed method optimises the arrangement of segmented imaging regions (SIRs), which are components of a panorama image, on the basis of the design data of the photomask pattern layout. The quantity of the line pattern segment, which is a clue to the connection in an overlapping region between adjoining SIRs and the connectability of any two SIRs, is evaluated. As a result of the optimisation, it is guaranteed that all SIR images can be connected theoretically. For 30 evaluation points, the maximum connection error of the SIR images was 1.5 nm in a simulation using pseudo-SEM images. The maximum total measurement error, which includes the connection error and CD measurement error from the panorama image, is estimated at 2.5 nm. This error was equivalent to about 1.4% of the photomask line width (target: 3%). The experiments using real SEM images demonstrate the effectiveness of the proposed method. It was visually confirmed that a large field, high-resolution and seamless panorama image can be generated. |
| Databáze: | OpenAIRE |
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