edfas.org 31 ELECTRONIC DEVICE FAILURE ANALYSIS | VOLUME 28 NO. 2 modes—continue to pose significant hurdles to model generalizability and robustness. The interpretability of complex models, particularly deep learning architectures, remains a barrier to trust and adoption in high-risk engineering settings. Additionally, integrating machine learning into traditional failure mode and effects analysis requires tailored frameworks and domain-specific data management strategies to ensure accuracy and relevance. As failure mechanisms become more subtle in advanced packaging and scaled nodes, the need for hybrid modeling approaches and physics-informed learning grows, demanding interdisciplinary collaboration and close partnership within the failure analysis ecosystem. EMERGING AREAS FA FOR PHOTONICS AND QUANTUM COMPUTING Photonic circuits offer superior power efficiency and bandwidth and are advancing rapidly in heterogeneous integration. Passive photonic devices can be integrated with silicon using standard die-level technologies, and photonic integrated circuits (PICs) can share planar areas with electronic ICs, though I/O components require hetero integration for lasers and photodiodes. Key challenges for PICs include optimizing couplers and managing signal loss, making fault analysis and localization an active area of development and a critical topic for 2D/3D system integration. As active photonic devices and quantum computing emerge, integrating cryogenic technologies and hybrid RF/PIC circuits will require new fault analysis approaches. Quantum entanglement will also introduce unique hardware assurance challenges for the community. HARDWARE ASSURANCE Techniques and tools routinely used in FA work and defect localization have been shown to also serve as potential attack vectors to recover secrets at the chip level. This fostered the development and implementation of various countermeasures. However, emerging techniques like quantum diamond microscopy, x-ray assisted device alteration, and e-beam probing may give researchers access to sensitive nodes in state-of-the art circuits. As such, their applications and limitations need to be fully evaluated. IC integrity in complex supply chains like the semiconductor industry remains a major concern for the different stakeholders. In-depth integrity analysis is a task of the highest complexity, requiring expertise across many fields such as sample preparation, imaging, computer vision, and machine learning to recover and verify a circuit from a manufactured chip. Each of these steps may still demand substantial advancement before achieving a robust solution. CONCLUSION In summary, ongoing advancements in silicon and packaging, disruptive test and design methods, and emerging fields like photonics and quantum technologies are reshaping the landscape of semiconductor integrated circuits. While these advancements offer unprecedented opportunities for the industry, they also introduce new technological challenges for fault isolation and failure analysis. Continued interdisciplinary research, strategic integration of emerging tools, and the development of robust workflows will be pivotal in ensuring that failure analysis keeps pace with the demands of modern semiconductor technology. Through the adoption of AI, workflow improvements, and strong collaborations and partnerships between tool developers, users, and research institutes, the community is grappling with these obstacles, striving to stay ahead and piece together the next generation of innovations in failure analysis. ACKNOWLEDGMENTS The Die-Level Fault Isolation Committee is genuinely committed to tackling the challenges outlined above by developing practical, forward-looking solutions. The committee members know the road ahead is complex, and while they do not have all the answers yet, they are working diligently to build a roadmap that reflects both the realities of the industry and the needs of the electronics failure analysis community. More detailed updates will be shared on ASM Connect as their work progresses. The author wants to sincerely thank every committee member for their dedication, thoughtful contributions, and deep expertise—none of this would be possible without their continued support and collaboration. Members of the Die-Level Fault Isolation Committee researched and co-authored this article. They include: Navid Asadi, Christian Boit, Edward Cole, Kristofor Dickson, Jayant D’Souza, Lesly Endrinal, Kent Erington, Rommel Estores, Szu Huat Goh, Kristof J.P. Jacobs, William Lo, Tommaso Melis, Zhongling Qian, VenkatKrishnan Ravikumar, Samuel Chef, Tom Tong, and Yan Pan.
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