Application of chemometrics to optical emission spectroscopy for plasma monitoring

Michael P. Splichal; Harold M. Anderson

doi:10.1117/12.56632

1 January 1992 Application of chemometrics to optical emission spectroscopy for plasma monitoring

Michael P. Splichal, Harold M. Anderson

Proceedings Volume 1594, Process Module Metrology, Control and Clustering; (1992) https://doi.org/10.1117/12.56632
Event: Microelectronic Processing Integration, 1991, San Jose, CA, United States

Abstract

Real-time plasma etch process monitoring, based on sensors which measure plasma properties that relate directly to desire etch features, is critical to the manufacturability of future-generation integrated microelectronics. This study reports on the development of spatially resolved optical emission spectroscopy tools and spectral signature analysis techniques which, taken together, show promise for meeting the need for such a sensor-based tool. This approach to plasma monitoring requires the development of optical emission calibration data sets, which in this case were obtained using the GEC Reference Cell plasma etch reactor (a RIE RF discharge system developed for interlaboratory comparisons). Systematic electrical probe measurements of the current and voltage waveform characteristics of Ar and CF4/CHF3 discharges in the Cell are reported and shown to be a sensitive indicator of both variations in Cell to Cell characteristics and process-induced variability within a Cell. Variations in the optical emission intensity show a near unity correlation with probe measurements if a broad spectrum of the emission is examined using multivariate statistical algorithms (chemometrics) and the spatial dependence of the emission is considered. Preliminary results involving further application of this spectral signature analysis technique to silicon dioxide etching are discussed.

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Michael P. Splichal and Harold M. Anderson "Application of chemometrics to optical emission spectroscopy for plasma monitoring", Proc. SPIE 1594, Process Module Metrology, Control and Clustering, (1 January 1992); https://doi.org/10.1117/12.56632

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