NDLI: Time series modeling of photosensitive BCB development rate for via formation applications

Content Provider	IEEE Xplore Digital Library
Author	Tae Seon Kim May, G.S.
Copyright Year	1999
Description	Author affiliation: Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA (Tae Seon Kim)
Abstract	Via formation is a critical process in multichip module (MCM) manufacturing, as it greatly impacts yield, density, and reliability. For via formation using photosensitive polymers such as benzocyclobutene (BCB), development is an extremely important step, and insuring adequate time for the completion of polymer dissolution is the key to defining the desired via pattern. To simultaneously optimize via yield and process throughput, the proper development time needs to be identified. However, it is difficult to determine the development endpoint because it is very sensitive to several factors. In this paper, a neural network based time series modeling scheme is developed and applied to determine the optimal endpoint for photosensitive BCB development. For on-line dissolution rate monitoring and development step analysis, the Lithacon 808 process analyzer is used. To characterize the development step, exposure dose energy and time series data consisting of previous film thicknesses are used to model expected film thicknesses at future times. Model prediction results are compared with experimental results, and it is shown that the neural time series model can effectively characterize the effects of changes in exposure dose energy on development endpoint.
Starting Page	355
Ending Page	361
File Size	838195
Page Count	7
File Format	PDF
ISBN	0780355024
ISSN	10898190
DOI	10.1109/IEMT.1999.804846
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1999-10-19
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Lithography Predictive models Semiconductor device modeling Manufacturing processes Multichip modules Polymers Neural networks Integrated circuit packaging Costs Application software
Content Type	Text
Resource Type	Article
Subject	Industrial and Manufacturing Engineering Electrical and Electronic Engineering

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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