Metal layer process characterization: statistical and computational methods for handling, interpreting, and reacting to inline critical dimension information

Joyce Oey; Patricia F. Mahoney Mack; Chris A. Mack

doi:10.1117/12.324404

27 August 1998 Metal layer process characterization: statistical and computational methods for handling, interpreting, and reacting to inline critical dimension information

Joyce Oey, Patricia F. Mahoney Mack, Chris A. Mack

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Proceedings Volume 3509, In-Line Characterization Techniques for Performance and Yield Enhancement in Microelectronic Manufacturing II; (1998) https://doi.org/10.1117/12.324404
Event: Microelectronic Manufacturing, 1998, Santa Clara, CA, United States

Abstract

A common challenge faced in many photolithographic processes is the patterning of photoresist on reflective substrates such as aluminum. One effect of the reflectivity of such substrates is linewidth variation known as reflective notching which severely impacts process latitude and device reliability. In recent years, strongly absorbing intermediate layers or ARCs, both organic and inorganic, have seen widespread implementation to control reflective notching. However, a more cost effective and immediate solution to reflective notching would be the application of a fast, high resolution dyed version of an i-line resist optimized for linewidth control over reflective topography. AMD's Fab solution to reflective notching was the implementation of Shipley's 3617M photoresist for all non- ARC metal layers. The process was qualified, implementation and monitored for two weeks at which time in-line data indicated: 1) a downward shift in the metal linewidths, 2) increased critical dimension variation, and 3) a critical dimension distribution statistically different from the previous photoresist process. This paper will present the methods used for handling, interpreting and reacting to in- line metal critical dimension data. Actual production data will be compared to PROLITH/2 simulated results, and corrective actions identified as well as lessons-learned summarized.

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Joyce Oey, Patricia F. Mahoney Mack, and Chris A. Mack "Metal layer process characterization: statistical and computational methods for handling, interpreting, and reacting to inline critical dimension information", Proc. SPIE 3509, In-Line Characterization Techniques for Performance and Yield Enhancement in Microelectronic Manufacturing II, (27 August 1998); https://doi.org/10.1117/12.324404

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KEYWORDS

Metals

Reflectivity

Semiconducting wafers

Photoresist processing

Critical dimension metrology

Photoresist materials

Cadmium

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