Title
Deep sub-wavelength metrology for advanced defect classification
Author
van der Walle, P (TNO)
Kramer, E. (TNO)
van der Donck, J.C.J. (TNO)
Mulckhuyse, W (TNO)
Nijsten, L. (TNO)
Bernal Arango, F.A. (TU Delft QN/Kuipers Lab; TNO)
de Jong, A. (TNO)
van Zeijl, E. (TNO)
Spruit, H. E.T. (TNO)
van den Berg, J.H. (TNO)
Nanda, G. (TU Delft QN/Kavli Nanolab Delft)
van Langen-Suurling, A.K. (TU Delft QN/Kavli Nanolab Delft; Kavli institute of nanoscience Delft)
Alkemade, P.F.A. (TU Delft QN/Kavli Nanolab Delft; Kavli institute of nanoscience Delft) 
Pereira, S.F. (TU Delft ImPhys/Optics)
Maas, D.J. (TNO)
Contributor
Lehmann, Peter (editor)
Osten, Wolfgang (editor)
Albertazzi Gonçalves, Armando (editor)
Date
2017
Abstract
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.
Subject
advanced defect classification
dark field microscopy
defect detection
defect review
latex sphere equivalent
Particle contamination
semiconductor
speckle
To reference this document use:
http://resolver.tudelft.nl/uuid:99097a4e-529e-466c-ab6d-6ed5c06a85a1
DOI
https://doi.org/10.1117/12.2272414
Publisher
SPIE, Bellingham, WA, USA
ISBN
978-1-510611030
Source
Optical Measurement Systems for Industrial Inspection X
Event
Optical Measurement Systems for Industrial Inspection X 2017, 2017-06-26 → 2017-06-29, Munich, Germany
Series
Proceedings of SPIE, 1605-7422, 10329
Part of collection
Institutional Repository
Document type
conference paper
Rights
© 2017 P van der Walle, E. Kramer, J.C.J. van der Donck, W Mulckhuyse, L. Nijsten, F.A. Bernal Arango, A. de Jong, E. van Zeijl, H. E.T. Spruit, J.H. van den Berg, G. Nanda, A.K. van Langen-Suurling, P.F.A. Alkemade, S.F. Pereira, D.J. Maas