Ring Oscillator-Based PreBond TSV Testing Method With Classification and Grading of Defects

The immaturity of manufacturing processes often leads to a high incidence of defects in through-silicon vias (TSVs). Prebond TSV testing is essential for optimizing the yield of chip-based integrated circuits. However, current testing methods are limited by their incomprehensive fault coverage and difficulty detecting subtle defects. Furthermore, these methods exhibit significant performance variability due to changes in process angle, power supply voltage, and temperature (PVT). To overcome these limitations, this paper introduces an innovative Ring Oscillator (RO)-based prebond test method specifically designed for TSVs, with a robust system for defect classification and grading. By sampling each node of the RO oscillating ring, the proposed method enhances the resolution of the Time-to-Digital Converter, thereby improving the defect detection capability. Additionally, a weak current source, constructed utilizing the unique properties of MOS transistors, enables the precise detection of open faults, resistive open defects with Ropen ≥ 1.5 K, and leakage defects with Rleak ≤ 10 G. To further mitigate the impact of PVT variations on test results, the paper integrates advanced machine learning techniques for defect classification and grading, providing valuable insights for fault bin classification and fault diagnosis. This innovative approach contributes significantly to the advancement of 3D IC reliability assessment.