The surface Cu flake particle generation mechanism during Cu Chemical Mechanical Planarization (CMP) process was studied to propose optimal tribological conditions. Cu flake defects are the main impact on yield and reliability in Logic Devices. Fig.1 shows typical Cu Flake images and their components. The particle components are copper and copper oxide based on EDX analysis with Cu flake sizes ranging from a hundred nm to a few um. Engineering polishing wafers with five kinds of pattern densities and three different  line widths were prepared to evaluate defect density changes and elucidate the effects of surface topography and geometry. All polishing experiments were performed on a 300 mm polisher (LKPS, AMAT) with Hitachi Cu Barrier Slurry (HS-915TS).  Defect density changes were calculated by two steps: 1) scanned with KLA-Tencor 2915 Bright Field Inspection Tool, 2) reviewed by Applied-Materials SEMVision with 30 nm horizontal resolution.

 Determining the defect generation mechanism was approached by three different methodologies. Firstly, wafer friction torque was analyzed to estimate the mechanical impact dependency of defect generation during the brushing part of the cleaning process with these different patterns. Usually, friction torque is a well-known method to check the macro-scale impact in the defect investigation process. However, there were no correlation between torque difference and defect density. It is assumed that the wafer level friction sensor could not detect the patterning pitch scale’s impact difference. Secondly, a nano-scale approaching method was utilized to investigate the Cu flake phenomena. Interestingly, the highest defect density showed in the smallest patterned density and in the 72 nm line width by repeatable tests. What it found was that the Cu protrusion amount, as shown in Fig.2, linearly decreases with pattern density, with 3 nm range of difference between the minimum and maximum pattern density. It could be suspected that a higher Cu protrusion profile may be one of the big distributors in making more mechanical impaction in sub 100 nm pitch scales. To verify protrusion volume effects, the slurry selectivity was changed to encourage more protrusion by changing the H₂O₂ mixing ratio. Experimental results showed that higher H₂O₂ resulted in a lower  defect density. Lastly, the sliding velocity effect was studied with three different conditions: 1.0, 1.2, and 1.35 m/s. Fig.3 clearly showed the density effect of flake generation with each patterning wafer. In particular, a higher pattern density did not show defect density changes during the sliding speed tests, while a lower density pattern had increasing defects with higher sliding speeds. These results can explain the Cu flake generation mechanism by mechanical impact force, e.g. higher velocity speed and higher shear force during wafer cleaning process. We conclude that lower speed and less pattern selectivity is preferable to reduce the Cu flake defect level to overcome various pattern densities in the real production. We will explain in detail the experimental results and mechanism in the presentation.