Hostname: page-component-78c5997874-s2hrs Total loading time: 0 Render date: 2024-11-14T06:38:42.137Z Has data issue: false hasContentIssue false

Statistical Analysis of the Influence of Thinning Processes on the Strength of Silicon

Published online by Cambridge University Press:  01 February 2011

Yu Yang
Affiliation:
yu.yang@imec.be, IMEC, Leuven, Belgium
Ricardo Cotrin Teixeira
Affiliation:
cotrin@imec.be, IMEC, Leuven, Belgium
Philippe Roussel
Affiliation:
roussel@imec.be, IMEC, Leuven, Belgium
Bart Swinnen
Affiliation:
swinnen@imec.be, IMEC, Leuven, Belgium
Bert Verlinden
Affiliation:
Bert.Verlinden@mtm.kuleuven.be, KUL, MTM, Leuven, Belgium
Ingrid De Wolf
Affiliation:
dewolf@imec.be, IMEC, Leuven, Belgium
Get access

Abstract

Wafer thinning, one of the key enabling techniques for 3D integration, is widely studied due to its impact on Si breakage strength. However, most studies only focused on the average strength, without checking the failure mechanisms. This may result in misleading conclusions and the mechanism of breakage is still ambiguous. In this paper, the mechanical strength of wafers that were thinned using different methods [rough grinding(RG), fine grinding(FE), plasma etching(PE), chemical mechanical polishing(CMP)] was evaluated statistically and through failure analysis. The results provide the industry guidance on their wafer thinning strategy. Si wafers were thinned down to 300μm by different thinning techniques: only RG; RG+FG; RG+FG+10μm CMP and RG+FG+10μm PE. Next the samples were diced into strips and the strength was tested using a 4-point bending test. The breakage strength of the dies was plotted in Weibull graphs and on wafer maps. Both RG and PE samples showed a strong bimodal distribution. On the other hand, both FG and CMP wafers showed a monomodal behaviour. This observation was unexpected and until now never reported in literature. The RG wafer has large surface grooves and is the weakest one, as expected. The bimodal distribution of the strength of RG-dies could be related to the direction of the grinding marks on the surface (along width or length of the Si strips). There is a direct correlation with the position of the dies on the wafer and the bimodal distribution. Samples with lines perpendicular to the tensile stress (along the width of the strips) are more vulnerable than the rest. The fracture on these samples propagates vertically from the ground surface, along the {110} plane. The others are stronger and break along the {111} plane. FG improves both the surface roughness and the strength compared to RG. The Weibull curve, with a monomodal behavior, shifts to a higher breakage strength, indicating that the effect of the grooves on the breakage strength is removed by FG. After CMP, the strength raises 17% compared to FG-Si due to the removal of surface roughness. Similarly, PE increases the average strength by 15% from FG. However, the Weibull plot shows that after PE, there is again a bimodal failure distribution. The weaker one falls on top of the FG distribution and the stronger one mixes up with the CMP. This indicates that although a large fraction of these samples have a similar strength as CMP, but some parts still have defects, probably local roughness related, that serve as easy initiation of fracture. This study shows that the orientation of the grinding marks plays an important role in determining the fracture plane and thus the strength. FG can efficiently remove this effect. We also showed for the first time that even after PE there is a bimodal strength distribution. Part of the dies has the same strength as the ones after CMP, but part of the population still has a lower strength.

Type
Research Article
Copyright
Copyright © Materials Research Society 2009

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

1. ITRS 2007 edition.Google Scholar
2. Wu, L., Chan, J. and Hsiao, C.S., ECTC 2003, 1463.Google Scholar
3. McLellan, N., et al., Transactions of the ASME, 126, 110 (2004).Google Scholar
4. Jiun, H.H., et al., Microelectron. Reliab., 46, 836 (2006).Google Scholar
5. Sun, W., et al., ECTC 2007, 1390.Google Scholar
6. Tsai, M.-Y. and Lin, C.S., IEEE T. Electron. Pack., 30, 106 (2007).Google Scholar
7. Swinnen, B., et al., IEDM 2006, 1.Google Scholar
8. Lu, J.-Q., et al., IITC 2003, 74.Google Scholar
9. Kurino, H., et al., IEDM 1999, 879.Google Scholar
10. Yang, Y., et al., Semicond. Sci. Tech., 23, 075038 (2008).Google Scholar
11. De Munck, K., et al., IEEE Electr. Device L., 29, 322 (2008).Google Scholar
12. Beery, I., Lev, U. and Sherman, S., J. Appl. Phys., 93, 2429 (2003).Google Scholar
13. Yeung, B. and Lee, T.-Y., IEEE T. Compon. Pack. T., 26, 423 (2003)Google Scholar