Ultrasonic Methods for Material and Failure Characterization

Research output: ThesisDoctoral ThesisResearch

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Abstract

Current trends in micro- and nano-electronics are More-than-Moore (MtM) technologies, enabling functions similar to the five human senses, all integrated in a single electronic device. This ongoing trend of increased functionality and miniaturization leads to increased complexity and failure risk of MtM components. Consequently, the realization of MtM technologies demands advanced failure and material characterization, where methods showing at-line or in-line potential are most beneficial. The material- and failure characterization in metallic and polymer coatings as well as in layered systems is of high relevance due to their vast applications. However, many state of the art methods are destructive (e.g. focused ion beam milling) or at least require the direct loading of the analysed sample for material characterization (e.g. the determination of the Young's modulus by nanoindentation). Concerning failure characterization, the challenges include the localization of the defect on and within the sample and the distinction between various failure modes. Moreover, the defects in MtM devices often show extensions down to the nm regime. In addition, the applied technique must be time- and cost efficient. In this thesis, the two ultrasonic methods laser induced ultrasound (LUS) and scanning acoustic microscopy (SAM) are used for material and failure characterization of MtM relevant devices. The LUS and the SAM methods are tested regarding their potentials concerning (1) the determination of elastic properties of thin film systems and (2) the detection of defects in MtM relevant components. A special focus lies on the potential for at-line or in-line inspection of the ultrasonic methods. Moreover, the SAM evaluations are supported by elastodynamic finite integration technique (EFIT) simulations. The LUS method is used for the material characterization of metallic and polymer thin films for MtM technologies. In addition, the step-wise characterization of multi-layered systems via LUS is discussed. The possibility to distinguish different deposited metallic coatings via LUS measurements is analysed and the sensitivity of surface acoustic waves to light exposure of polymer coatings is demonstrated. For these LUS analyses, surface acoustic waves (SAWs) are excited on the sample by short laser pulses and detected using a second continuous wave laser. In layered systems, the SAW phase velocity can depend on the frequency. This dispersion relation (obtained from the LUS measurement) can also be calculated. By fitting the theoretical dispersion to the experimentally evaluated curve, material properties can be extracted from the SAW propagation. Alternatively, the SAW velocity can be used directly for material monitoring. The SAM analysis of delaminated printed circuit boards (PCBs) is presented in this work. Although the acoustic failure analysis is complicated by the multi-layered build up of the PCBs, an “indirect failure detection” was successfully applied. Moreover, the detection of subsurface cracks with extensions below the lateral and axial resolution limit of the SAM in through silicon vias (TSVs) – highly relevant MtM components – is carried out. The focus lies on the automatized failure detection via pattern recognition algorithms on the one hand and on the excitation of additional wave modes for failure detection on the other hand. The advantages of the low frequency excitation of additional wave modes - in contrast to high frequency SAM measurements - are discussed in detail. Moreover, SAM is used for material characterization, performing V(z) analyses, and the results are compared to the LUS outcome. Furthermore, the sound propagation during SAM measurements is simulated using EFIT. The results presented in this work are corroborated via variety of other state of the art characterization techniques (e.g. high resolution X-Ray computed tomography, scannin

Details

Translated title of the contributionUltraschall Methoden für die Material- und Fehlercharakterisierung
Original languageEnglish
QualificationDr.mont.
Awarding Institution
Supervisors/Advisors
  • Brunner, Roland, Assessor A (internal)
  • Paltauf, Günther, Assessor B (external), External person
Publication statusPublished - 2018