Thermal Sub-circuit Research Articles

Scalable Charge-Based Compact Model for Drain Current in Fin-Shaped GaN HEMTs

We present a novel charge-based compact model for drain current in fin-shaped GaN high-electron-mobility transistors (Fin-HEMTs). A positive threshold voltage shift is observed in Fin-HEMTs due to better gate control of the channel. The combined effect of top and side gates on the channel charge density is studied with the help of detailed TCAD simulation. For the first time, a closed-form expression for 2-D electron gas (2-DEG) density in Fin-HEMTs is derived. The fin width dependence of the 2-DEG current is modeled in a unique way by considering the modified gate capacitance and threshold voltage in Fin-HEMTs. The total drain current is modeled as the sum of 2-DEG and double-gate field effect transistor (FET) currents. In addition, the total gate capacitance including the side-gate capacitance for fin structure is also formulated. The model is generic and can be used for different fin geometries using the proposed equivalent circuits as demonstrated. A fin-width-dependent thermal resistance model is proposed and included in the drain current model using a thermal subcircuit. The proposed model is completely analytical and does not require any iteration or fitting parameters in contrast to the available models discussed in the literature. Our model shows excellent agreement with the state-of-the-art experimental data.

Modeling the Gradual RESET of Phase Change Memory With Confined Geometry

This work develops a model of the temperature and resistance for the RESET of confined phase change memory (PCM). The confined PCM, unlike the mushroom type, has heating inside the cell and higher resistance sensitivity to active region size. The ideal temperature profile is derived from a steady-state heat conduction formulation based on a quasi-3D approach. A thermal subcircuit is then proposed to implement the heating module, considering the thermoelectric effect (TEE) and temperature dependence of phase change materials, to obtain the active region size. The resistance of the irregular active region is then calculated using an integral method. Calibrated TCAD simulations and experimental data are used to verify the model with desired scalability and accuracy.

An improved temperature-dependent large signal model of microwave GaN HEMTs**Project supported by the National Natural Science Foundation of China (No. 61106115).

Accurate modeling of the electrothermal effects of GaN electronic devices is critical for reliability design and assessment. In this paper, an improved temperature-dependent model for large signal equivalent circuit modeling of GaN HEMTs is proposed. To accurately describe the thermal effects, a modified nonlinear thermal sub-circuit which is related not only to power dissipation, but also ambient temperature is used to calculate the variations of channel temperature of the device; the temperature-dependent parasitic and intrinsic elements are also taken into account in this model. The parameters of the thermal sub-circuit are extracted by using the numerical finite element method. The results show that better performance can be achieved by using the proposed large signal model in the range of −55 to 125 °C compared with the conventional model with a linear thermal sub-circuit.

Compact RF non-linear electro thermal model of SiGe HBT for the design of broadband ADC's

The design of high speed integrated circuits heavily relies on circuit simulation and requires compact transistor models. This paper presents a non-linear electro-thermal model of SiGe heterojunction-bipolar transistor (HBT). The non-linear model presented in this paper uses a hybrid π topology and it is extracted using IV and S-parameter measurements. The thermal sub-circuit is extracted using low-frequency S-parameter measurements. The model extraction procedure is described in detail. It is applied here to the modeling of npn SiGe HBTs. The proposed non-linear electro-thermal model is expected to be used for the design of high-speed electronic functions such as broadband analog digital converters in which both electrical and thermal aspects are engaged. The main focus and contribution of this paper stands in the fact that the proposed non-linear model covers wideband-frequency range (up to 65 GHz).

A Nonlinear Electro-Thermal Scalable Model for High-Power RF LDMOS Transistors

A new nonlinear charge-conservative scalable dynamic electro-thermal compact model for laterally defused MOS (LDMOS) RF power transistors is described in this paper. The transistor is characterized using pulsed I-V and S-parameter measurements, to ensure isothermal conditions. A new extrinsic network and extrinsic parameter-extraction methodology is developed for high-power RF LDMOS transistor modeling, using manifold deembedding by electromagnetic simulation, and optimization of the extrinsic network parameter values over a broad frequency range. The intrinsic model comprises controlled charge and current sources that have been implemented using artificial neural networks, designed to permit accurate extrapolation of the transistor's performance outside of the measured data domain. A thermal sub-circuit is coupled to the nonlinear model. Large-signal validation of this new model shows a very good agreement with measurements at 2.14 GHz.

An Empirical Large-Signal Model for SiC MESFETs With Self-Heating Thermal Model

An empirical large-signal model for high-power microwave silicon-carbide MESFETs capable of predicting self-heating thermal behavior is presented. A generalized drain-current equation based on pulsed-gate IV characteristics measuring up to 2 A and 58 V is presented along with its dependence on temperature. A thermal subcircuit with a nonlinear thermal resistance characterized by a dc method is used to model the temperature behavior of the device. The effect of substrate trapping is modeled as a gate-source voltage correction. The complete drain-current model accurately predicts pulsed-gate and pulsed-gate-and-drain IV characteristics for various quiescent biases, as well as static IV characteristics. The complete large-signal model is shown to accurately predict S -parameters, large-signal output, and input reflected power across biases and frequencies, and third-order intermodulation products.