Scalable X-Ray Characterization for Device Reliability and Failure Analysis

(22:10 + Q&A) Jeff Gelb, Sigray —  The increasing complexity of modern electronic devices has placed unprecedented demands on characterization techniques. As device architectures evolve toward multi-layered 3D integrations and transistor dimensions continue to shrink, conventional analytical methods must be complemented by advanced approaches for precise structural and materials characterization. X-ray techniques have emerged as a key solution due to their non-destructive nature and ability to reveal buried interfaces with high spatial resolution. In this presentation, we review the role of X-ray methods across 2D, 2.5D, and 3D modalities, highlighting recent advancements that extend these capabilities into the resolution & throughput regimes that facilitate practical, scalable inspection & metrology workflows. We also discuss the growing importance of high-resolution analytical techniques such as X-ray fluorescence (XRF), which offer both elemental and structural insights and are increasingly adaptable for production-scale inspection. Finally, we introduce a novel concept: X-ray Assisted Device Alteration (XADA)—a 3D, spatially selective approach that expands upon traditional laser-based alteration (LADA) techniques, with particular relevance to emerging backside power delivery architectures.
Bio: Jeff Gelb is Director of X-Ray Microscopy at Sigray in Benicia, California, focused on next-generation 3D X-ray imaging for semiconductor failure analysis and in-line part inspection. He studied physics at UC Santa Barbara and joined Xradia in 2006, working with multi-scale 3D tomography, which carried forward into his later work with correlative microscopy at ZEISS. Jeff completed a Master’s degree in Materials Engineering at San Jose State in 2017, with a research emphasis in developing non-destructive characterization routines for commercial lithium-ion batteries. Jeff joined Sigray in 2017 and is excited about the future of 3D imaging, with much of his current work focused on automation, software, and data capture and processing workflows.

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