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Proceedings Paper

Technique to analyze large-area surface roughness of a wafer using TXRF
Author(s): Brooke Noack; Tim Z. Hossain
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Paper Abstract

Determining the roughness of a wafer surface inside a wafer fabrication plant would be advantageous in solving process problems in semiconductor device manufacturing. Currently, there is not a technique in the fab that will measure the large area surface roughness accurately and non-destructively. Traditionally Atomic Force Microscopy (AFM)1 has been the method of choice for surface roughness analysis. However, AFM typically measures roughness in a micro-area (e.g. 5 μm x 5μm). We have developed a new technique with Total Reflection X-ray Fluorescence (TXRF)2 for the determination of surface roughness using a large area scan. TXRF is used primarily to find trace metal contamination on the surface of a wafer. 3 In the TXRF measurement a secondary fluorescence signal is obtained following irradiation with a primary x-ray beam. We have found that plotting the primary scatter beam (e.g. Au L13 counts per second) versus the secondary fluorescent x-rays (e.g. Si counts per second), a trend is obtained that is linear and specific for a particular wafer. The slope of this linear trend is strongly dependent on the roughness of the wafer surface as determined by AFM. By comparing the slopes of these lines we have found that an increase in slope relates to an increase in roughness. The data has shown that this relationship is independent of the surface type. Polysilicon, oxide and metal stack wafers with varying surface roughness (e.g. AFM) have been studied with the TXRF.

Paper Details

Date Published: 27 August 1998
PDF: 7 pages
Proc. SPIE 3509, In-Line Characterization Techniques for Performance and Yield Enhancement in Microelectronic Manufacturing II, (27 August 1998); doi: 10.1117/12.324416
Show Author Affiliations
Brooke Noack, Advanced Micro Devices, Inc. (United States)
Tim Z. Hossain, Advanced Micro Devices, Inc. (United States)


Published in SPIE Proceedings Vol. 3509:
In-Line Characterization Techniques for Performance and Yield Enhancement in Microelectronic Manufacturing II
Sergio A. Ajuria; Tim Z. Hossain, Editor(s)

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