Contactless pre-bond TSV fault diagnosis using duty-cycle detectors and ring oscillators

Defects in TSVs due to fabrication steps decrease the yield and reliability of 3D stacked ICs, hence these defects need to be screened early in the manufacturing flow. We propose a non-invasive method for pre-bond TSV test and diagnosis that does not require TSV probing. We use open TSVs as capacitive loads of their driving gates and measure the propagation delay by means of ring oscillators. Defects in TSVs cause variations in their RC parameters and therefore lead to variations in the propagation delay. By measuring these variations, we can detect resistive open and leakage faults. In addition, we use duty-cycle detectors to measure the duty cycle of the oscillation signal. These measurements provide additional information for fault analysis and hence increase the diagnosis accuracy. We exploit different voltage levels to increase the sensitivity of the test and its robustness against random process variations. We also present a method to create a regression model based on artificial neural networks to predict the fault size. As input, this model uses both the oscillation period and the duty cycle measured at multiple different voltage levels. The model classifies the type of the fault and predicts its size. Moreover, the regression model can effectively determine whether a TSV has both leakage and resistive-open defects. Results on fault-diagnosis effectiveness are presented through HSPICE simulations using realistic models for a 45nm CMOS technology. The estimated DfT area cost of our method is negligible for dies of realistic size.