Deep sub-wavelength metrology for advanced defect classification
| Autor: | van der Walle, P, Kramer, E., van der Donck, J.C.J., Mulckhuyse, W, Nijsten, L., Bernal Arango, F.A., de Jong, A., van Zeijl, E., Spruit, H. E.T., van den Berg, J.H., Nanda, G., van Langen-Suurling, A.K., Alkemade, P.F.A., Pereira, S.F., Maas, D.J., Lehmann, Peter, Osten, Wolfgang, Albertazzi Gonçalves, Armando |
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| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
Dark field microscopy
Scanner Materials science Latex sphere equivalent High Tech Systems & Materials 02 engineering and technology 01 natural sciences Signal Defect review Speckle pattern Optics Particle contamination Speckle 0103 physical sciences Surface roughness Nanotechnology 010302 applied physics Defect detection NI - Nano Instrumentation OPT - Optics TS - Technical Sciences Industrial Innovation business.industry Orientation (computer vision) Semiconductor 021001 nanoscience & nanotechnology Aspect ratio (image) Metrology Advanced defect classification Azimuth Nano Technology 0210 nano-technology business |
| Zdroj: | SPIE Optical Metrology 2017, Munich, Germany, 26–29 June 2017 Optical Measurement Systems for Industrial Inspection X |
| Popis: | Particle defects are important contributors to yield loss in semi-conductor manufacturing. Particles need to be detected and characterized in order to determine and eliminate their root cause. We have conceived a process flow for advanced defect classification (ADC) that distinguishes three consecutive steps; detection, review and classification. For defect detection, TNO has developed the Rapid Nano (RN3) particle scanner, which illuminates the sample from nine azimuth angles. The RN3 is capable of detecting 42 nm Latex Sphere Equivalent (LSE) particles on XXX-flat Silicon wafers. For each sample, the lower detection limit (LDL) can be verified by an analysis of the speckle signal, which originates from the surface roughness of the substrate. In detection-mode (RN3.1), the signal from all illumination angles is added. In review-mode (RN3.9), the signals from all nine arms are recorded individually and analyzed in order to retrieve additional information on the shape and size of deep sub-wavelength defects. This paper presents experimental and modelling results on the extraction of shape information from the RN3.9 multi-azimuth signal such as aspect ratio, skewness, and orientation of test defects. Both modeling and experimental work confirm that the RN3.9 signal contains detailed defect shape information. After review by RN3.9, defects are coarsely classified, yielding a purified Defect-of-Interest (DoI) list for further analysis on slower metrology tools, such as SEM, AFM or HIM, that provide more detailed review data and further classification. Purifying the DoI list via optical metrology with RN3.9 will make inspection time on slower review tools more efficient. |
| Databáze: | OpenAIRE |
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