This project extends a 2023 initiative focused on the reverse engineering of semiconductor

devices, a process that critically compares the "as-built" semiconductor chip with its "as designed" specifications. This comparison is pivotal in identifying any fabrication discrepancies

that might degrade the chip's performance. At the heart of this analysis is the GDSII file format, essential for encapsulating design data for manufacturing and verification. The challenge lies in

extracting GDSII data from a completed chip, which necessitates high-resolution imaging to

unravel the chip's intricate layers, followed by sophisticated image processing techniques for

segmentation and data extraction. A crucial step in this process is delayering, traditionally

achieved through Focused Ion Beam (FIB) techniques renowned for their precision but criticized

for their slow pace, which prolongs the reverse engineering timeline and complicates rapid issue

identification in failure analysis. Although mechanical polishing and chemical etching present

alternatives, they fall short in precision, controllability, and repeatability, largely depending on

the operator's skill. To address these challenges, our study introduces an innovative approach

that significantly accelerates the delayering process. By employing a controllable, automated

femtosecond laser scanning beam for material removal, we achieve a rapid process that surpasses traditional FIB techniques in speed, while minimizing thermal damage and preserving

the circuitry's integrity for further analysis. However, femtosecond laser processing introduces

its own set of challenges, particularly when exposing buried chip layers for volumetric imaging.

The varied interactions between the laser and different material compositions can lead to uneven layer exposure, complicating the extraction of comprehensive circuitry information. Our research addresses this by presenting two novel methods. The first leverages a technique we previously developed for creating high-precision volumetric images of printed circuit boards (PCBs), assigning accurate RGB or grayscale values to voxels within a 3D grid to account for the non-flat surfaces produced by laser delayering (we applied an RGB version of this to chips in the 2023 project and we plan to apply a high-resolution grayscale version of it in the 2024 project). This enables precise 3D reconstructions of the target chip volume. The second method combines ultrashort pulsed laser delayering with FIB polishing to achieve completely flat surfaces for single 2D image exposure. This hybrid approach utilizes the speed of laser delayering and the precision of FIB polishing, optimizing sample preparation for reverse engineering and failure analysis. Subsequently, we apply image processing and machine learning techniques to extract the chip's circuitry from these images, a critical step for verification, validation, and reverse engineering objectives.