Cu-to-Cu direct bonding was successfully achieved in 10 s with 〈111〉-oriented nanotwinned Cu (nt-Cu) bumps in ambient N 2 . The bonding temperature and pressure were 300 °C and 90 MPa, respectively. A nearly void-free interface and a low bump resistance of 4.9 mΩ can be observed after a short-time bonding process. Besides, longer bonding times of 60 s and 30 s were employed, but the resistances of the Cu joints did not decrease significantly when the bonding time increased to 60 s. However, the nt-Cu columnar grains started to recrystallize during the 60 s bonding and started detwinning in 10 s bonding. Yet, the bonding interface remained under such a short bonding time.
We adopted (111)-oriented Cu with high surface diffusivity to achieve low-temperature and low-pressure Cu/SiO2 hybrid bonding. Electroplating was employed to fabricate arrays of Cu vias with 78% (111) surface grains. The bonding temperature can be lowered to 200 °C, and the pressure is as low as 1.06 MPa. The bonding process can be accomplished by a 12-inch wafer-to-wafer scheme. The measured specific contact resistance is 1.2 × 10−9 Ω·cm2, which is the lowest value reported in related literature for Cu-Cu joints bonded below 300 °C. The joints possess excellent thermal stability up to 375 °C. The bonding mechanism is also presented to provide more understanding on hybrid bonding.
The failure mechanisms of Cu–Cu bumps under thermal cycling test (TCT) were investigated. The resistance change of Cu–Cu bumps in chip corners was less than 20% after 1000 thermal cycles. Many cracks were found at the center of the bonding interface, assumed to be a result of weak grain boundaries. Finite element analysis (FEA) was performed to simulate the stress distribution under thermal cycling. The results show that the maximum stress was located close to the Cu redistribution lines (RDLs). With the TiW adhesion layer between the Cu–Cu bumps and RDLs, the bonding strength was strong enough to sustain the thermal stress. Additionally, the middle of the Cu–Cu bumps was subjected to tension. Some triple junctions with zig-zag grain boundaries after TCT were observed. From the pre-existing tiny voids at the bonding interface, cracks might initiate and propagate along the weak bonding interface. In order to avoid such failures, a postannealing bonding process was adopted to completely eliminate the bonding interface of Cu–Cu bumps. This study delivers a deep understanding of the thermal cycling reliability of Cu–Cu hybrid joints.
Three-dimensional integrated circuit (3D IC) technologies have been receiving much attention recently due to the near-ending of Moore’s law of minimization in 2D IC. However, the reliability of 3D IC, which is greatly influenced by voids and failure in interconnects during the fabrication processes, typically requires slow testing and relies on human’s judgement. Thus, the growing demand for 3D IC has generated considerable attention on the importance of reliability analysis and failure prediction. This research conducts 3D X-ray tomographic images combining with AI deep learning based on a convolutional neural network (CNN) for non-destructive analysis of solder interconnects. By training the AI machine using a reliable database of collected images, the AI can quickly detect and predict the interconnect operational faults of solder joints with an accuracy of up to 89.9% based on non-destructive 3D X-ray tomographic images. The important features which determine the “Good” or “Failure” condition for a reflowed microbump, such as area loss percentage at the middle cross-section, are also revealed.
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