This thesis presents an automated methodology to calibrate the substrate profile for accurate prediction of substrate parasitics using Green's function based extractors. The technique requires fabrication of only a few test structures and results in an accurate three layered approximation of a heavily doped epitaxial silicon substrate. The obtained substrate resistances are accurate to about 10% of measurements. Advantages and limitations of several common measurement techniques used to measure substrate z-parameters and resistances are discussed. A new and accurate z-parameter based macro-model has been developed that can be used up to a few GHz for P��� for contacts that are as close as 2��m. This enhanced model also addresses the limitations of previous models with regards to implementation aspects and ease of integration in a CAD framework. Limitations of this modeling approach have been investigated. The calibration methodology can be used along with the scalable macromodel for a qualitative pre-design and pre-layout estimation of the digital switching noise that couples though the substrate to sensitive analog/RF circuits. / Graduation date: 2004

Graduation date: 2004

3D design is being recognized widely as the next BIG thing in system integration. However, design and analysis tools for 3D are still in infancy stage. Power supply noise analysis is one of the critical aspects of a design. Hence, the area of noise analysis for 3D designs is a key area for future development. The following research presents a new parasitic RLC modeling technique for 3D chips containing TSVs as well as a novel optimization algorithm for power-ground network of a 3D chip with the aim of minimizing noise in the network. The following work also looks into an existing commercial IR drop analysis tool and presents a way to modify it with the aim of handling 3D designs containing TSVs.

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