Prof. Ehrenfried Zschech
Brandenburg University of Technology, Germany
Title: High-resolution X-ray Imaging for Industrial Process Monitoring and Quality Control
Abstract: High-resolution X-ray imaging provides nondestructive characterization capabilities on opaque objects, observing features with sizes across a range of length scales, down to several 10 nanometers using lens-based transmission X-ray microscopy (TXM). X-ray computed tomography (XCT), characterized by a sample thickness/resolution value of ~ 103, and subsequent 3D data reconstruction, is an efficient approach to study the 3D morphology of natural and engineered hierarchically structured systems and materials. Because of the ability of micro-XCT and nano-XCT to reveal structural characteristics, to determine deviations from a well-defined standard, or to observe kinetic processes, they are potential imaging techniques for micro- and nano-structured objects, but also for industrial process monitoring and quality control [1]. In this talk, typical applications of high-resolution XCT are categorized into 3 groups: 1) Creation of 3D digital images of the complete interior structure of an opaque object, e.g., a natural object or an engineered composite or
skeleton material (typically for fundamental research), 2) Monitoring industrial processes and defect inspection (e.g., in the semiconductor industry), and 3) Observing kinetic processes in objects, both in materials synthesis and in materials ageing, important for industrial quality control and reliability engineering. These different categories of applications have different requirements for the accuracy of the 3D reconstruction and for the time-to-data [2]. While the highest possible resolution is requested for group 1, data acquisition and data analysis time are essential for group 2. To get highresolution 3D information of the complete interior structure of an opaque object using lens-based laboratory nano-XCT requires a thorough data analysis, e.g., the application of deep convolutional neural networks, for denoising andmitigation of artefacts. On the micro- and nanoscale, thermomechanical instability of tool components and object motion, center of rotation misalignment, and inaccuracy in the detector position require computational efforts [3]. Advanced 3D reconstruction methodologies consider these unavoidable effects during the image acquisition [4].
The rapid evolution of advanced semiconductor technologies, including technologies for heterogeneous 3D integration of ICs and chiplet architectures, presents significant challenges for metrology, defect inspection, and physical failure analysis (PFA). The application of nano-XCT as a highly reliable inspection method requires a balance between
throughput and fault detection (i.e., measurement and reconstruction accuracy) [5]. Ways for a drastic acquisition speed increase are high-brilliance laboratory X-ray sources, the application of AI algorithms for new image acquisition protocols, and high-speed data processing. An outlook for a seamless workflow for advanced package FA and defect inspection, that combines acoustic and X-ray techniques to auto-detect and auto-classify defects, with the goal to improve throughput and defect detectability, will be presented [6]. Finally, kinetic studies, e.g., of reliability-limiting degradation processes in microchips, provide the opportunity to establish appropriate risk mitigation strategies to avoid catastrophic failure. The nano-XCT imaging of the microcrack evolution points out possible directions to ensure the requested mechanical robustness of microchips and of heterogeneously integrated chiplets, applying advanced packaging technologies [7].
[1] E Zschech, Handbook of Nondestructive Evaluation 4.0, 1377 (2025)
[2] M. V. Chukalina, ITiVS 2, 3 (2025)
[3]
E. Topal et al., BMC Mater. 2, 1 (2020), Sci. Rep. 10, 1 (2020)
[4] K. Bulatov et al., Nanomaterials 11, 2524 (2021)
[5] EDFAS Electronic Device Failure Analysis Technology Roadmap, ASM International (2023)
[6] E. Zschech et al., ISMP IRSP Busan, Korea (2024)
[7] K. Kutukova et al., Materials & Design 221, 110946 (2022)
Biodata: Ehrenfried Zschech is a consultant with hands-on experience in the fields of advanced materials, nanotechnology, and microelectronics, as well as process control and quality assessment. He holds honorary professorships in Nanomaterials at Brandenburg University of Technology Cottbus-Senftenberg and in Nanoanalysis at Dresden University of Technology, and he is a Guest Chair Professor at Southeast University, Nanjing, China. His activities include high-resolution Xray imaging and the development of customized solutions for a broad range of applications, including package failure analysis, metrology, and inspection in microelectronics. Ehrenfried Zschech received his Dr. rer. nat. degree from Dresden University of Technology. He held several management positions at Airbus, Advanced Micro Devices, Fraunhofer, and the start-up deepXscan. Ehrenfried Zschech is a Member of the European Academy of Science (EurASc) and a Member of the German National Academy of Science and Engineering (ACATECH). In 2019, he was awarded the FEMS European Materials Gold Medal, in 2023 the DGM Pioneer Award, and with the Roland Mitsche Prize.
Prof. Jeff Kuhn
University of Hawaii, USA
Title: The ExoLife Finder (ELF) and Small ExoLife Finder Telescope Projects.
Abstract: The Laboratory for Innovation in OptoMechanics (LIOM) at the IAC is designing the world’s largest telescope – it will look for signs of life on the nearest exoplanets. To build this 35m-scale diameter telescope will depend critically on new technologies, in particular machine learning (ML). This telescope, called the ExoLife Finder (ELF), is unlike other ground-based telescopes because it is optimized from the onset to achieve narrow field-of-view observations of optical and IR sources with enormous photometric dynamic range. For example, an Earthlike (habitable zone) exoplanet will be a billion times fainter than its host solar-like star. The ELF is 10 years away from operating but its prototype, the Small ELF (SELF), is being built now on Teide on Tenerife in the Canary Islands. SELF is a 3.5m fixed aperture Fizeau interferometer formed from 15 0.5m diameter 2-mirror off-axis telescopes. It has a total mass that is only about 20% of the total moving mass of a conventional telescope of the same diameter. As an interferometer it requires ultraprecise mechanical alignment (accurate to about 10nm over the length of the structure) and it uses many actuated mechanical degrees of freedom to enforce this alignment in an environment of changing gravity, temperature, and stochastic driving forces (like wind). Controlling these optomechanical degrees of freedom (DOF) requires machine learning tools. Finally the data such a telescope collects also depends on ML tools to interpret and understand the exoplanet reflected light, and ultimately to generate images of the surfaces of planets around stars that are within about 30 light years of the Sun. This talk will summarize the motivation and progress toward designing and building the SELF and ELF, and the ML systems that are essential for enabling these optomechanical systems.
Biodata: Jeff’s 1981 PhD is in physics from Princeton. He’s currently emeritus professor of Astronomy at the University of Hawaii, where he was founder of the Advanced Technology Research Center of the Institute for Astronomy, and its director for 10 years. He is currently a distinguished senior researcher at the Instituto de Astrofisica de Canarias (IAC) and the ERA Chair and leader of the Laboratory for Innovation in Optomechanics at the IAC. He started the optical technology company MorphOptic, Inc. and the non-profit Planets Foundation. His publications encompass many areas of solar, stellar and gravitational physics, polarimetry, IR optical and instrumentation technology, and signal detection. Kuhn is a Sloan Foundation grant recipient, winner of the Humboldt Prize (Germany), and Regents Prize (Hawaii).
He believes new astronomical (and remote sensing) instrumentation is paced by advances in materials and information technologies. These are accelerating in step with “Moores Law” much like the growth in digital computing. The astronomical instruments and telescopes being conceived and built today have complexity and capability that we could barely imagine a decade ago. Kuhn has been involved in the design and realization of such large and small astronomical instruments for more than 30 years.
Prof. Pietro Ferraro
Institute of Applied Sciences & Intelligent Systems Campi Flegrei, Italy
Title: TOMOFLOW: Intelligent Computational Holographic Microscopy Meets Microfluidics for
Next-Generation Imaging
Abstract: The rapid analysis of small, dynamic, and heterogeneous particles—such as live cells, microplastics, and aquatic microorganisms—poses a major challenge in biomedical and environmental research. TOMOFLOW presents a novel platform that synergizes intelligent computational microscopy with microfluidic technology to enable high-throughput, label-free 3D holographic imaging of microscopic objects in flow. By reconstructing refractive index tomograms in real-time and leveraging multimodal analysis driven by AI it oXers unprecedented capability and steps forward automation in identifying and characterizing subcellular structures, synthetic particles, and microbial species. This integrative approach sets the stage for next-generation imaging tools in cytometry, ecotoxicology, and microbiology.
Biodata: Pietro Ferraro is Director of Research at the CNR Institute of Applied Sciences and Intelligent Systems (ISASI), Italy. He served as ISASI Director from 2014 to 2019 and President of CNR Research Area in Pozzuoli from 2012 to 2019. Ferraro has held leadership roles in various organizations and worked as Principal Investigator with Alenia Aeronautics from 1988 to 1993. His research spans holography, microscopy, biomedical sensing, micro-nanostructures, non-destructive testing and optical sensors, with over 350 journal papers, 20,000 citations and 14 patents. A Fellow of both Optica and SPIE, and Senior Member of IEEEE he received the SPIE Gabor Award and served on the Scientific and Technical Committee for the Italian Space Agency from 2018 to 2023.
Prof. Peng Gao
Xidian University, China
Title: Sparse Scanning Structured
Illumination Microscopy (SS-SIM) for Super-resolution
Imaging of Thick Samples
Abstract: Structured illumination
microscopy (SIM) is a powerful super-resolution optical
technique most suitable for live sample imaging.
However, conventional SIM suffers from limited
penetration depth (tens of micrometers) since its
wide-field illumination is susceptible to sample
scattering. To overcome this limitation, we developed a
sparse scanning structured illumination microscopy
(SS-SIM) as a super-resolution imaging technique for
thick sample imaging. SS-SIM utilizes sparse fringe
patterns generated by resonant scanning of a focused
laser spot and synchronized intensity modulation. SS-SIM
achieves a spatial resolution of 154 ± 12 nm, ~1.6-fold
enhancement over conventional wide-field microscopy,
across an imaging depth range from 0 to 200 μm for
single-photon and 600 μm for two-photon excitation. We
envision that our technique will find applications in
imaging cells, tissues, and organisms, as well as other
areas of the life sciences.
Biodata: Prof. Dr. Peng Gao, studied Physics and received his Ph.D. at the Xi’an Institute of Optics and Precision Mechanics (XIOPM), CAS, in 2011. He was a “Humboldt Fellow” in University Stuttgart (2012-2014) and Marie-Curie Fellow (IEF) in KIT (2014-2018). He is currently a PI at Xidian University. His group focuses on developing quantitative phase microscopy and super-resolution optical microscopy techniques for biology. So far, he has authored over 100 peer-reviewed papers published in journals, including Nat. Photonics, Adv. Opt. Photon. Some of his publications were highlighted by tens of international media, such as Science Daily, Physics News, and so on. He is currently one of the associate editors of Optics and Laser Technology (OLT) and Frontiers in Physics,