Paper
5 April 2007 Line width measurement below 60nm using an optical interferometer and artificial neural network
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Abstract
We have recently described a technique for optical line-width measurements. The system currently is capable of measuring line-width down to 60 nm with a precision of 2 nm, and potentially should be able to measure down to 10nm. The system consists of an ultra-stable interferometer and artificial neural networks (ANNs). The former is used to generate optical profiles which are input to the ANNs. The outputs of the ANNs are the desired sample parameters. Different types of samples have been tested with equally impressive results. In this paper we will discuss the factors that are essential to extend the application of the technique. Two of the factors are signal conditioning and sample classification. Methods, including principal component analysis, that are capable of performing these tasks will be considered.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Chung W. See, Richard J. Smith, Michael G. Somekh, and Andrew Yacoot "Line width measurement below 60nm using an optical interferometer and artificial neural network", Proc. SPIE 6518, Metrology, Inspection, and Process Control for Microlithography XXI, 65181F (5 April 2007); https://doi.org/10.1117/12.712278
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KEYWORDS
Signal to noise ratio

Interferometers

Principal component analysis

Artificial neural networks

Photons

Point spread functions

Classification systems

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