CMOS technology is expected to enter the 10nm regime for future integrated circuits (IC). Such aggressive scaling leads to vastly increased variability, posing a grand challenge to robust IC design. Variations in CMOS are often divided into two types: intrinsic variations and process-induced variations. Intrinsic variations are limited by fundamental physics. They are inherent to CMOS structure, considered as one of the ultimate barriers to the continual scaling of CMOS devices. In this work the three primary intrinsic variations sources are studied, including random dopant fluctuation (RDF), line-edge roughness (LER) and oxide thickness fluctuation (OTF). The research is focused on the modeling and simulation of those variations and their scaling trends. Besides the three variations, a time dependent variation source, Random Telegraph Noise (RTN) is also studied. Different from the other three variations, RTN does not contribute much to the total variation amount, but aggregate the worst case of Vth variations in CMOS. In this work a TCAD based simulation study on RTN is presented, and a new SPICE based simulation method for RTN is proposed for time domain circuit analysis. Process-induced variations arise from the imperfection in silicon fabrication, and vary from foundries to foundries. In this work the layout dependent Vth shift due to Rapid-Thermal Annealing (RTA) are investigated. In this work, we develop joint thermal/TCAD simulation and compact modeling tools to analyze performance variability under various layout pattern densities and RTA conditions. Moreover, we propose a suite of compact models that bridge the underlying RTA process with device parameter change for efficient design optimization.

Negative bias temperature instability (NBTI) and channel hot carrier (CHC) are important reliability issues impacting analog circuit performance and lifetime. Compact reliability models and efficient simulation methods are essential for circuit level reliability prediction. This work proposes a set of compact models of NBTI and CHC effects for analog and mixed-signal circuit, and a direct prediction method which is different from conventional simulation methods. This method is applied in circuit benchmarks and evaluated. This work helps with improving efficiency and accuracy of circuit aging prediction.

To extend the lifetime of complementary metal-oxide-semiconductors (CMOS), emerging process techniques are being proposed to conquer the manufacturing difficulties. New structures and materials are proposed with superior electrical properties to traditional CMOS, such as strain technology and feedback field-effect transistor (FB-FET). To continue the design success and make an impact on leading products, advanced circuit design exploration must begin concurrently with early silicon development. Therefore, an accurate and scalable model is desired to correctly capture those effects and flexible to extend to alternative process choices. For example, strain technology has been successfully integrated into CMOS fabrication to improve transistor performance but the stress is non-uniformly distributed in the channel, leading to systematic performance variations. In this dissertation, a new layout-dependent stress model is proposed as a function of layout, temperature, and other device parameters. Furthermore, a method of layout decomposition is developed to partition the layout into a set of simple patterns for model extraction. These solutions significantly reduce the complexity in stress modeling and simulation. On the other hand, semiconductor devices with self-feedback mechanisms are emerging as promising alternatives to CMOS. Fe-FET was proposed to improve the switching by integrating a ferroelectric material as gate insulator in a MOSFET structure. Under particular circumstances, ferroelectric capacitance is effectively negative, due to the negative slope of its polarization-electrical field curve. This property makes the ferroelectric layer a voltage amplifier to boost surface potential, achieving fast transition. A new threshold voltage model for Fe-FET is developed, and is further revealed that the impact of random dopant fluctuation (RDF) can be suppressed. Furthermore, through silicon via (TSV), a key technology that enables the 3D integration of chips, is studied. TSV structure is usually a cylindrical metal-oxide-semiconductors (MOS) capacitor. A piecewise capacitance model is proposed for 3D interconnect simulation. Due to the mismatch in coefficients of thermal expansion (CTE) among materials, thermal stress is observed in TSV process and impacts neighboring devices. The stress impact is investigated to support the interaction between silicon process and IC design at the early stage.

In this thesis two methodologies have been proposed for evaluating the fault response of analog/RF circuits. These proposed approaches are used to evaluate the response of the faulty circuit in terms of specifications/measurements. Faulty response can be used to evaluate important test metrics like fail probability, fault coverage and yield coverage of given measurements under process variations. Once the models for faulty and fault free circuit are generated, one needs to perform Monte Carlo sampling (as opposed to Monte Carlo simulations) to compute these statistical parameters with high accuracy. The first method is based on adaptively determining the order of the model based on the error budget in terms of computing the statistical metrics and position of the threshold(s) to decide how precisely necessary models need to be extracted. In the second method, using hierarchy in process variations a hybrid of heuristics and localized linear models have been proposed. Experiments on LNA and Mixer using the adaptive model order selection procedure can reduce the number of necessary simulations by 7.54x and 7.03x respectively in the computation of fail probability for an error budget of 2%. Experiments on LNA using the hybrid approach can reduce the number of necessary simulations by 21.9x and 17x for four and six output parameters cases for improved accuracy in test statistics estimation.