No abstract

In manufacturing of microelectronic components, non-destructive failure analysis methods are important for quality control. These non-destructive methods enable rapid defect localization which then guides micro-structural investigations involving destructive sample preparation. Scanning acoustic microscopy (SAM) is a powerful tool for the inspection of internal structures in optically opaque materials. Depth-specific information can be extracted and applied to create two- and three-dimensional images without the need for time consuming tomographic scan procedures. While traditional SAM imaging of the signal intensity is very valuable, it leaves most of the potential of acoustic microscopy unused. The aim of the current work was to develop comprehensive analysis algorithms to utilize the full potential of SAM and thus to extend the range of its applications. Examples representing different application fields were investigated in the current study. The examples include advanced flip-chip devices, bonded wafer pairs, solder tape connectors of a photovoltaic solar panel and high density chip-to-chip interconnects relevant for 3D integration. Progress achieved during this work can be divided into four categories: Signal Analysis and Parametric Imaging, Signal Analysis and Defect Evaluation, Image Processing and Resolution Enhancement and acoustic GHz microscopy (GHz-SAM). For the first three categories, data acquisition was performed using a commercially available scanning acoustic microscope equipped with several ultrasonic transducers covering the frequency range from 15 to 175 MHz. In the fourth category, data acquisition was performed employing a prototype of a novel acoustic GHz microscopy tool which is currently under development into a commercial system. In the first three categories, recorded acoustic data were subjected to sophisticated algorithms operating in time, frequency and spatial domains for performing signal and image analysis. Acoustic microscopy, combined with such advanced signal and image processing algorithms, proved to be a powerful tool for non-destructive inspection

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