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The Determination of Copper Composition Profiles in Semiconductor Device Aluminum Interconnect Electromigration Test Lines using Electron Probe Microanalysis (EPMA)

Published online by Cambridge University Press:  02 July 2020

J.M. Oparowski
Affiliation:
Digital Semiconductor, Digital Equipment Corporation (DEC), Hudson, MA01749
T.S. Sriram
Affiliation:
Digital Semiconductor, Digital Equipment Corporation (DEC), Hudson, MA01749
V. Ambrose
Affiliation:
Digital Semiconductor, Digital Equipment Corporation (DEC), Hudson, MA01749
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Extract

Extensive long range transport of copper has been observed in polycrystalline aluminum-copper (Al-Cu) interconnects subjected to accelerated electromigration testing. Cu depletion is believed to be the rate limiting factor for electromigration damage accumulation. It is not clear if this is also the case for Al-Cu interconnects with bamboo/near-bamboo microstructures. In order to understand this phenomenon, Cu transport under electromigration conditions in bamboo microstructures has to be characterized quantitatively. This paper describes the procedure used to determine Cu distributions on a series of bamboo test structures subjected to accelerated electromigration (EM) testing. Copper composition profiles were determined for these structures through the use of electron probe microanalysis (EPMA) techniques and customized corrections for non-standard interaction volumes.

Aluminum (0.5 wt.% Cu) interconnect test line structures were fabricated with four metal layers and surrounding silicon dioxide dielectric. Following EM testing, the samples were deprocessed to expose the test lines at metal layer three, as shown in Figure 1.

Type
Microscopy of Semiconducting and Superconducting Materials
Copyright
Copyright © Microscopy Society of America

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References

References:

1.Hu, C-K., Ho, P.S. and Small, M.B., Journal of Applied Physics. 74(2), 969 (1993)CrossRefGoogle Scholar
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3. The Authors would like to acknowledge the contributions of M. Foley (DEC) and CO. Schiebl for their assistance with sample preparation and the SeSAME modeling program.Google Scholar