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Advanced microelectronics metrology increasingly depends on how the sample is prepared before inspection. In heterogeneous packages, the region of interest may be buried beneath combinations of mold compound, silicon, copper, redistribution layers, dielectrics, underfill, and organic substrate materials. The measurement challenge is therefore not only one of imaging resolution, but also one of physical access: the sample must be opened to the correct level, the exposed structures must remain interpretable, and the preparation geometry must provide useful views of internal layers and interfaces. This paper presents a metrology-driven sample-preparation workflow using the TESCAN FemtoChisel ultrashort-pulsed laser platform. The workflow combines femtosecond laser machining, intelligent multigas processing, laser protective layer strategies, imaging feedback, and AI-enabled process development. The broader platform capability includes controlled package opening, layer exposure, access-window creation, cross-section preparation, and correlative workflows with optical, confocal, SEM/FIB, and X-ray imaging. In this paper, the experimental results focus specifically on demonstrations relevant to metrology access: controlled laser delayering. Specifically, it is shown that the laser process can expose selected package levels and provide intermediate inspection states. Through creation of inverted pyramid structures we demonstrate the ability to stop at the layer of interest. The results support a preparation-to-measurement framework in which laser machining is used not simply to remove material, but to create measurement-ready sample states. Intelligent multigas processing and protective-layer concepts expand the usable process window by improving debris management and boundary preservation. AI-enabled process development and correlative navigation provide a path toward more repeatable and target-aware preparation. Together, these elements position FemtoChisel as a platform for creating controlled access geometries that support advanced package metrology, failure analysis, and process development.
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Anaei et al. (2026) studied this question.
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