In-line etching process control using dynamic scatterometry

Abstract

In-line process control in microelectronics manufacturing requires real-time and non-invasive monitoring techniques. Among the different metrology techniques, scatterometry, based on the analysis of ellipsometric signatures (i.e stokes coefficients vs. wavelength) of the light scattered by a patterned structures, seems to be well adapted. Traditionally, the problem of defining the shape and computing the signature is dealt with modal methods and is called direct problem. On the opposite, the inverse problem allows to find the grating shape thanks to an experimental signature acquisition, and can not be solved as easily. Different classes of algorithms have been introduced (evolutionary, simplex, etc.) to address this problem, but the method of library searching seems to be the most attractive technique for industry. This technique has many advantages that will be presented in this article, however the main limitation in real-time context comes from the short data acquisition time for different wavelengths. Indeed, the lack of data leads to the method failure and several database patterns can match the experimental data. In this article, a technique for real time reconstruction of grating shape variation using dynamic scatterometry is presented. The different tools to realize this reconstruction, such as Modal Method by Fourier Expansion, regularization technique and specific software and hardware architectures are then introduced. Results issued from dynamic experiments will finally illustrate this paper.

S-Genius, a universal software platform with versatile inverse problem resolution for scatterometry

“…The technical expertise in this field covers at the same time simulation works for MMFE coding, [38] real-time application, [39,40] scatterometric porosimetry studies, [41] and uncertainty assessment. [37] Since a decade, the MMFE coding has been written for simulation: for example, embedded defaults characterisation on Extreme-UV lithography masks may be detected by diffraction fingerprint analysis [42].…”

Automatic inspection of a residual resist layer by means of self-organizing map

“…Furthermore, it is adapted for the in-line characterization process. 6,7 This technique involves an inverse problem resolution, which can be performed by a different approaches, such as classic optimization, 8 metaheuristcs 9 methods, regression, or library searching methods. 10 Artificial neural networks (ANNs) have also been introduced as multilayer perceptrons (MLP).…”