TY - CONF A1 - Mrkwitschka, Paul A1 - Mieller, Björn A1 - Rabe, Torsten A1 - Markötter, Henning ED - Petzow, G. ED - Mücklich, F. T1 - Machine learning assisted characterization of a Low Temperature Cofired Ceramic (LTCC) module measured by synchrotron computed tomography N2 - The 5G technology promises real time data transmission for industrial processes, autonomous driving, virtual and augmented reality, E-health applications and many more. The Low Temperature Co-fired Ceramics (LTCC) technology is well suited for the manufacturing of microelectronic components for such applications. Still, improvement of the technology such as further miniaturization is required. This study focuses on the characterization of inner metallization of LTCC multilayer modules, especially on the vertical interconnect access (VIA). Critical considerations for this characterization are delamination, pore clustering in and at the edge of the VIA, deformation, and stacking offset. A LTCC multilayer consisting of a glassy crystalline matrix with silver based VIAs was investigated by synchrotron x-ray tomography (CT). The aim of this study is to propose a multitude of structural characteristic values to maximize the information gained from the available dataset. Data analysis has been done with the open source software ImageJ as well as several additional plugins. The high-resolution CT data was evaluated through 2D slices for accessibility reasons. The segmentation of all 2000 slices to assess the different regions e.g. pores, silver and glass ceramic was done by a supervised machine learning algorithm. A quantitative evaluation of shape, deformation, and porosity of the VIA with respect to its dimensions is presented and the suitability of the characterization approach is assessed. T2 - 54. Metallographie Taagung CY - Online meeting DA - 16.09.2020 KW - Machine Learning KW - LTCC KW - Synchrotron Tomography PY - 2020 SN - 978-3-88355-422-8 VL - 54 SP - 136 EP - 141 PB - Deutsche Gesellschaft für Materialkunde e.V CY - Sankt Augustin AN - OPUS4-51298 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Markötter, Henning A1 - Dayani, Shahabeddin A1 - Mishurova, Tatiana A1 - Eddah, Mustapha A1 - Mieller, Björn A1 - Böttcher, Nils A1 - Bruno, Giovanni T1 - Tomographic Imaging Capabilities with hard X-Rays at BAMline (Bessy II) N2 - The BAMline at the synchrotron X-ray source BESSY II (Berlin, Germany) is supporting researchers especially in materials science. As a non-destructive characterization method, synchrotron X-ray imaging, especially tomography with hard X-Rays, plays an important role in structural 3D characterization. The imaging capabilities allow for in-situ and operando experiments. In this presentation the equipment, data handling pipeline as well as various examples from material science are presented. T2 - Correlative Materials Characterization Workshop 2023 CY - Brno, Czech Republic DA - 09.11.2023 KW - Tomography KW - X-ray imaging KW - Li-ion battery PY - 2023 AN - OPUS4-58958 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -