CAM-Workshop Program 2025

Day 1 (20. May 2025)

Session A: Welcome and Keynotes

09:00 – 09:40 Prof. Dr. Erica Lilleodden /  Frank Altmann Fraunhofer IMWS (DE) Welcome
09:40 – 10:00 Albert Heuberger Fraunhofer IIS (DE) Keynote: The APECS Pilot Line: European Chiplet Innovation
10:00 – 10:40 Kristof Croes IMEC (BE) Keynote: Reliability challenges of Silicon Photonic devices and its related Failure Analysis challenges
10:40 – 11:20 Mikel Azpeitia Urquia ST Microelectronics (IT) Keynote: MEMS: Smart sensors for a sustainable AI

Session B: MEMS & Sensors

11:20 – 11:40 Holger Pfaff Infineon (DE) Micromechanics without walking the plank- MEMS characterization at Infineon Regensburg
11:40 – 12:00 Roy Knechtl University of Applied Sciences Schmalkalden (DE) Understanding Wafer Bonded MEMS by (Failure) Analysis
12:00 – 12:20 Martin Stermitz AMS-Osram (AT) Pinpointing Leakage Defects in TSVs: A Refined Failure Analysis Approach
12:20 – 12:40 Bernd Hähnlein CIS (DE) Implantation related crystallographic defects in pressure sensors

Session C: Emerging Fault Isolation Techniques

14:00 – 14:20 Neel Leslie Thermo Fisher Scientific (US) E-beam Probing and E-beam-Assisted Device Alteration (EADA) for Fault Isolation in PowerVia and Advanced Technology Nodes
14:20 – 14:40 Michael Di Battista Varioscale (US) Innovative Approaches to Ultra Thinning Silicon to Enabling New Insights in IC Failure Analysis
14:40 – 15:00 Pascal Limbecker GlobalFoundries (DE) Challenges for Nanoprobing of 22nm FDSOI devices
15:00 – 15:20 Sebastian Brand Fraunhofer IMWS (DE) Precise 3D Defect Localization in quantitative Lock-in Thermography by analyzing the spatial phase distribution
15:20 – 15:40 Shimpei Tominaga Hamamatsu (JP) Application to a failure analysis of Visible ThermoDynamic ® Imaging
15:40- 16:00 Marc van Veenhuizen NXP (NL) RF-LIT background and use cases

Session D: NN

16:40 – 18:00 NN

Day 2 (21. May 2025)

Session E: Tutorial

08:00 – 09:00 Enrico Zanoni University Padua (IT) Tutorial: Deep level effects, failure modes and mechanisms of GaN HEMTs; current understanding and open questions

Session F: GaN Electronics

09:40 – 10:20 Thomas Detzel Infineon Technologies Austria AG (AT) Keynote: Gallium Nitride Power Devices and Systems: Benefits and Industrial Realization
10:20 – 10:40 Victor Sizov Nexperia (NL) Cascode GaN devices for high power application
10:40 – 11:00 Aidan Taylor Infineon Villach (AT) A direct correlation of dislocation characterization in GaN by scanning electron and scanning transmission electron microscopes
11:00 – 11:20 Marc Fouchier Attolight (CH) Characterisation of crystalline defects in GaN using cathodoluminescence
11:20 – 11:40 Michél Simon-Najasek Fraunhofer IMWS (DE) Novel approach of combined planar and cross-sectional defect analysis of stressed normally-on HEMT devices with leaky Schottky gates
11:40 – 12:00 Steve Knebel X-FAB (DE) Reliability characterization challenges for wide bandgap power electronics
12:00 – 12:20 Sebastian Fritzsche Heraeus (DE) Towards affordable GaN power modules – advanced interconnect materials & solutions

Session G: AI Applications and FA Workflows

13:40 – 14:20 Konstantin Schekotihin  University Klagenfurt (AT) Keynote: Towards a Sustainable AI Lifecycle in FA Labs
14:20 – 14:40 Sebastian Stolwijk  BOSCH (DE) Automated Infrared Microscopy Workflow – Image Acquisition and AI Anomaly Detection
14:40 – 15:00 Kenneth Braakmans NXP (NL) Implementation of AI/ML in wirebonding processes
15:00 – 15:20 Bernhard Fichtl  ZEISS Microscopy (DE) AI assisted FA workflows
15:20 – 15:40 Amit-Kumar Choudhary Matworks (DE) Digital workflows and ML techniques to optimize failure analysis in microelectronics
15:40 – 16:00 Lorenz Heinemann Fraunhofer IMWS (DE) Simplifying ML-Based Signal Analysis in FA by Removing Equipment Related Transfer Properties
16:00 – 16:20 David Stefan Kleindiek Kleindiek Nanotechnik (DE) Enhancing Semiconductor Nanoprobing procedures with AI-Driven Tip Detection
16:20 – 16:40 Christoph Maier Infineon Technologies (DE) Failure Analysis Ontology for structuring FA knowledge and meta data in a machine and human readable format