A Novel Approach for Fault Detection and Failure Analysis of CMOS Copper Metal Stacks

TL;DR

This paper presents a detailed analysis of fault signatures in large-scale CMOS copper metal stacks used in monolithic pixel sensors, highlighting a novel detection approach and mitigation strategies to improve yield.

Contribution

It introduces a new analysis method for fault detection in CMOS copper metal stacks and demonstrates its application to large wafer-scale sensors for the ALICE experiment.

Findings

Recurrent fault signatures were identified across multiple wafers.

A mitigation strategy was successfully implemented to reduce faults.

The analysis method improved understanding of yield issues in large CMOS stacks.

Abstract

For the Inner Tracking System 3 (ITS3) upgrade, the ALICE experiment at CERN requires monolithic active pixel sensors of dimensions up to 97~mm$\,\times\,$266~mm, occupying a large fraction of a 300 mm wafer. To manufacture such a wafer-scale device, larger than the single design reticle size, stitching is employed. The MOnolithic Stitched Sensor (MOSS) is a prototype silicon pixel sensor of 14~mm$\,\times\,$259~mm size with the primary goal of understanding the stitching technique and yield. Given the large size, high yield is paramount for the ITS3 sensors, and an in-depth yield characterization was performed on these MOSS sensors. In a collaborative effort, the foundry adapted the metal stack to the requirements of the project, but recurrent fault signatures were discovered with various frequencies across all 20 wafers tested, and correlated through dedicated measurements and analyses. Following these findings, the foundry implemented a mitigation strategy to avoid the issue in the future. This article does not describe process details but concentrates on the measurements and analysis method.