Semiconductor Device Modeling and Simulation for Electronic Circuit Design

This chapter covers different methods of semiconductor device modeling for electronic circuit simulation. It presents a discussion on physics-based analytical modeling approach to predict device operation at specific conditions such as applied bias (e.g., voltages and currents); environment (e.g., temperature, noise); and physical characteristics (e.g., geometry, doping levels). However, formulation of device model involves trade-off between accuracy and computational speed and for most practical operation such as for SPICE-based circuit simulator, empirical modeling approach is often preferred. Thus, this chapter also covers empirical modeling approaches to predict device operation by implementing mathematically fitted equations. In addition, it includes numerical device modeling approaches, which involve numerical device simulation using different types of commercial computer-based tools. Numerical models are used as virtual environment for device optimization under different conditions and the results can be used to validate the simulation models for other operating conditions

Modeling of gallium nitride transistors for high power and high temperature applications

Wide bandgap (WBG) semiconductors such as GaN and SiC are emerging as promising alternatives to Si for new generation of high efficiency power devices. GaN has attracted a lot of attention recently because of its superior material properties leading to potential realization of power transistors for high power, high frequency, and high temperature applications. In order to utilize the full potential of GaN-based power transistors, proper device modeling is essential to verify its operation and improve the design efficiency. In this view, this research work presents modeling and characterization of GaN transistors for high power and high temperature applications. The objective of this research work includes three key areas of GaN device modeling such as physics-based analytical modeling, device simulation with numerical simulator and electrothermal SPICE model for circuit simulation. The analytical model presented in this dissertation enables understanding of the fundamental physics of this newly emerged GaN device technology to improve the operation of existing device structures and to optimize the device configuration in the future. The numerical device simulation allows to verify the analytical model and study the impact of different device parameters. An empirical SPICE model for standard circuit simulator has been developed and presented in the dissertation which allows simulation of power electronic circuits employing GaN power devices. The empirical model provides a good approximation of the device behavior and creates a link between the physics-based analytical model and the actual device testing data. Furthermore, it includes an electrothermal model which can predict the device behavior at elevated temperatures as required for high temperature applications.Includes bibliographical reference

Code-level modeling of the Hodgkin -Huxley neuron model using an open source version of SPICE

There have been numerous studies presented in the literature demonstrating proof of principle neural-electronic circuitry. Some of these studies involve simulations of neural detection using synthetic electronic circuitry, while others involve simulations of neural excitation using external electronics. A common feature of these studies is the simplicity of the overall circuit topology. Some of these studies implement the circuit equations in conventional numerical ordinary differential equation solvers. This process involves the algebraic manipulation of the circuit equations which is a tedious process for all but the simplest circuit topologies. As the overall complexity of the network topology increases, the numerical solver approach quickly becomes intractable necessitating an alternate implementation strategy. SPICE implementations of the Hodgkin-Huxley neuron model have sought to remedy this problem. There have been multiple studies associated with implementing the Hodgkin-Huxley model in the open source circuit simulator, SPICE. In this dissertation, a novel implementation of a portable SPICE device model developed using the Hodgkin-Huxley active membrane model is implemented using the code-level modeling functionality of an open source version of SPICE. The model is validated by comparison with standard Hodgkin-Huxley model simulations including gating variable dynamics simulations, accommodation, anodebreak excitation, and others. A further validation study is carried out demonstrating two blocking phenomenon described in the literature. The device model fully parameterizes the Hodgkin-Huxley membrane model to include temperature, internal and external concentrations used in the Nernst equations, and other user specified parameter values. This parameterization allows for making changes to the underlying neuron model rapidly and with minimal implementation complexity. The novelty and robustness of the modeling approach described herein is based on the ease of implementation. A wide variety of active membranes can be simulated using this code model approach. These biologically realistic components can be integrated with artificial electronic components allowing for the simulation of hybrid neuralelectronic circuitry under the SPICE simulation platform. These types of hybrid circuit simulations are not currently achievable using other neural simulators such as NEURON or GENESIS. While this implementation uses the Hodgkin-Huxley neuron model with its known limitations, the process of developing the device model can be used to implement any neuron model which can be described mathematically

Physics-based large-signal sensitivity analysis of microwave circuits using technological parametric sensitivity from multidimensional semiconductor device models

The authors present an efficient approach to evaluate the large-signal (LS) parametric sensitivity of active semiconductor devices under quasi-periodic operation through accurate, multidimensional physics-based models. The proposed technique exploits efficient intermediate mathematical models to perform the link between physics-based analysis and circuit-oriented simulations, and only requires the evaluation of dc and ac small-signal (dc charge) sensitivities under general quasi-static conditions. To illustrate the technique, the authors discuss examples of sensitivity evaluation, statistical analysis, and doping profile optimization of an implanted MESFET to minimize intermodulation which makes use of LS parametric sensitivities under two-tone excitatio

Effective electrothermal analysis of electronic devices and systems with parameterized macromodeling

We propose a parameterized macromodeling methodology to effectively and accurately carry out dynamic electrothermal (ET) simulations of electronic components and systems, while taking into account the influence of key design parameters on the system behavior. In order to improve the accuracy and to reduce the number of computationally expensive thermal simulations needed for the macromodel generation, a decomposition of the frequency-domain data samples of the thermal impedance matrix is proposed. The approach is applied to study the impact of layout variations on the dynamic ET behavior of a state-of-the-art 8-finger AlGaN/GaN high-electron mobility transistor grown on a SiC substrate. The simulation results confirm the high accuracy and computational gain obtained using parameterized macromodels instead of a standard method based on iterative complete numerical analysis

Large-signal device simulation in time- and frequency-domain: a comparison

The aim of this paper is to compare the most common time- and frequency-domain numerical techniques for the determination of the steady-state solution in the physics-based simulation of a semiconductor device driven by a time-periodic generator. The shooting and harmonic balance (HB) techniques are applied to the solution of the discretized drift-diffusion device model coupled to the external circuit embedding the semiconductor device, thus providing a fully nonlinear mixed mode simulation. The comparison highlights the strong and weak points of the two approaches, basically showing that the time-domain solution is more robust with respect to the initial condition, while the HB solution provides a more rapid convergence once the initial datum is close enough to the solution itsel