Automated Analysis of AFM Data of High-Density Cu Pad for Fine Pitch Wafer-to-Wafer (W2W) and Chip-to-Wafer (C2W) Hybrid Bonding

Jiakai Chen, Yong Chyn Ng, D. K. Mishra, K. Chui
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Abstract

With the advancement of 3D packaging, hybrid bonding is the most widely explored technology for heterogeneous integration and stacking of dies. For the hybrid bonding, prior measurement of the surface roughness, dielectric erosion, and dishing/protrusion of the copper bond pads is critical to check the quality of the fabricated wafers. Generally, atomic force microscopy (AFM) is used to collect the surface morphology of the wafers, and then the manual measurement is done for each scanned file which is quite time-consuming. Therefore, in this article, an automated method of analysis of AFM data was developed in Python to measure critical surface parameters on the wafers used in hybrid bonding. The Python code was used to measure the surface roughness, dishing/protrusion of bond pads with different shapes, i.e., circular and square. The use of the code provides a quick, efficient, first-order analysis methodology for evaluating the quality of the bonding surface, thereby, significantly reducing the manual time required in data crunching.
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高密度铜衬垫的AFM数据自动分析用于小间距晶对晶(W2W)和芯片对晶(C2W)混合键合
随着三维封装技术的发展,杂化键合技术是目前应用最为广泛的异质集成和叠层技术。对于混合键合,预先测量铜键合垫的表面粗糙度、介电侵蚀和盘状/突出是检查制造晶圆质量的关键。通常采用原子力显微镜(AFM)采集晶圆片的表面形貌,然后对每个扫描文件进行人工测量,这非常耗时。因此,本文在Python中开发了一种自动分析AFM数据的方法,用于测量用于混合键合的晶圆上的关键表面参数。Python代码用于测量不同形状的键垫,即圆形和方形的表面粗糙度,盘状/突出度。该代码的使用提供了一种快速、高效的一阶分析方法来评估粘接表面的质量,从而大大减少了数据处理所需的人工时间。
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