A Study of Through-Silicon-Via ( TSV ) Induced Transistor Variation by

As continued scaling becomes increasingly difficult, 3D integration has emerged as a viable solution to achieve higher bandwidth and power efficiency. Through-siliconvias (TSVs), which directly connect stacked structures die-to-die, is one of the key techniques enabling 3D integration. The process steps and physical presence of TSVs, however, may generate a stress-induced thermal mismatch between TSVs and the silicon bulk. These effects could further perturb the performance of nearby electronic structures, particularly transistors, diodes, and associated circuits. This thesis presents a comprehensive study to characterize, analyze and model the impact of TSV-induced stress impact on device and circuit performance and its interaction with polysilicon and shallow-trench-isolation (STI) layout pattern density. A test chip is designed with multiplexing test circuits providing measurements of key parameters of a large number of devices. These devices under test (DUTs) have layouts that explore a range of TSV and device layout choices in the design of experiments (DOEs). The test chip uses a scan chain approach combined with low-leakage and low-variation switches and Kelvin sensing connections, which provide access to detailed analog device characteristics in large arrays of test devices. A test circuit and an I0ff measurement method is designed to perform off-chip wafer probe testing measurement. In addition, a finite element analysis model is constructed to mimic realistic TSV structures and processes. A complete flow and methodology to analyze transistor characteristics and circuit performance under the influence of TSV stress is proposed. An efficient algorithm is also proposed to simulate full-chip circuit variation under the impact of TSV stress based on a grid partition approach. Test cases corresponding to the aforementioned test chip are simulated for comparison with measurement data. Thesis Supervisor: Duane S. Boning Title: Professor of Electrical Engineering and Computer Science

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