High Electron Mobility Transistor Model Research Articles

Radiation effects modeling of InP-based HEMT based on neural networks

This paper has proposed a novel radiation effects modeling methodology based on neural networks for InP-based high-electron-mobility transistors (HEMTs). 2 MeV proton radiation has been performed with dose of 1 × 1012 H+/cm2, 5 × 1012 H+/cm2, 1 × 1013 H+/cm2, 5 × 1013 H+/cm2, 1 × 1014 H+/cm2. The radiation neural network models were comparatively constructed based on Feedforward Neural Network (FNN), Recurrent Neural Network (RNN), and Long Short-Term Memory (LSTM). Results indicate that the LSTM network outperforms the FNN and RNN networks in the modeling for both drain-source current (IDS) and S-parameters, which demonstrates superior prediction accuracy with smaller fitting error. The proposed modeling approach offers an accurate characterization for the radiation effects of InP-based HEMT devices, without the need to consider the complex degradation process associated with radiation, thus providing practical guidelines for the space applications of such devices.

Temperature- and gate voltage-dependent I–V modeling of GaN HEMTs based on ASM-HEMT

Abstract In this paper, a temperature and gate voltage dependent current-voltage (I-V) model for Gallium nitride (GaN) high electron mobility transistors (HEMTs) devices is studied. In order to help researchers and designers simulate devices in the absence of experimental data and improve parameter extraction efficiency, the temperature and gate voltage dependence of mobility are discussed and incorporated into the proposed model which is revised from the standard advanced SPICE model (ASM) for GaN HEMTs. The mobility variations with gate voltage from -2 V to 6 V and temperature from 10 K to 1000 K are analyzed. The simulation results of our model are compared with the standard ASM-HEMT model, and the output and transfer characteristics of the device from 270 K to 420 K are simulated. Thereby, our model may simulate various applications of GaN HEMTs at different gate voltages and temperatures in the early stages of design and research.

A novel small-signal equivalent circuit model for GaN HEMTs incorporating a dual-field-plate

An accurate and novel small-signal equivalent circuit model for GaN high-electron-mobility transistors (HEMTs) is proposed, which considers a dual-field-plate (FP) made up of a gate-FP and a source-FP. The equivalent circuit of the overall model is composed of parasitic elements, intrinsic transistors, gate-FP, and source-FP networks. The equivalent circuit of the gate-FP is identical to that of the intrinsic transistor. In order to simplify the complexity of the model, a series combination of a resistor and a capacitor is employed to represent the source-FP. The analytical extraction procedure of the model parameters is presented based on the proposed equivalent circuit. The verification is carried out on a 4 × 250 μm GaN HEMT device with a gate-FP and a source-FP in a 0.45 μm technology. Compared with the classic model, the proposed novel small-signal model shows closer agreement with measured S-parameters in the range of 1.0 to 18.0 GHz.

Incorporation of total ionizing dose effects into a compact model for p-GaN gate high electron mobility transistors

Total ionizing dose (TID) characteristics of p-GaN gate high electron mobility transistors (HEMTs) under different bias conditions are explored in this work. Potential mechanism accounting for the TID response of p-GaN gate HEMTs is analyzed, based on which a TID effects model is developed. The TID effects model describes the relationship among threshold voltage of p-GaN gate HEMTs, total radiation dose, and electric field inside the p-GaN cap layer. Furthermore, an approach incorporating the TID effects model into Advanced Spice Model for HEMT (ASM-HEMT) is proposed, the reliability of which is validated by the well-fitted modeled results in comparison with the measured ones. This approach makes it possible to probe into the impact of TID effects on p-GaN gate HEMTs from the perspective of circuit level, which provides a basis for the follow-up GaN-based circuit design.

A Scalable Knowledge-Based Neural Network Model for GaN HEMTs With Accurate Trapping and Self-Heating Effects Characterization

In this article, a scalable knowledge-based neural network (KBNN) large-signal model of gallium nitride (GaN) high-electron-mobility transistors (HEMTs) with accurate trapping and self-heating effects characterization is developed. An improved empirical drain current model is proposed and added to the neural network as prior knowledge, thereby establishing the drain current model, including self-heating effect. A new empirical equation is proposed to model the buffer-related trapping effect more accurately. Taking Angelov capacitance models as prior knowledge, the KBNN capacitance models are completed. Moreover, the scaling characteristics of the proposed KBNN model are studied. The developed model has been fully verified by different sizes of GaN HEMTs. Good agreement between the model simulation results and the measurement data, including current–voltage ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$I$</tex-math> </inline-formula> – <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$V$</tex-math> </inline-formula> ), <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$S$</tex-math> </inline-formula> -parameters, power characteristics, and load-pull data, confirms the effectiveness of the proposed model. The proposed scalable KBNN model is fast and accurate and would be useful for accurate large-signal modeling of large gate periphery GaN HEMTs for high-power radio frequency (RF) applications.

A distributed thermal model of GaN HEMT considering nonlinear thermal conductivity and PCB effect

A distributed thermal model for analyzing the heat distribution of GaN high electron mobility transistor (HEMT) is presented in this paper. The thermal resistance calculation of multi-gate GaN HEMT with nonlinear thermal conductivity is derived. Considering the heat conduction of PCB and the nonlinear thermal conductivity, the model developed in COMSOL realizes the consistency between the simulation results and the measurement results. Based on the model, the surface and internal temperatures can be extracted for the thermal resistance calculation. The proposed method combined model simulation with numerical calculation will be helpful for designers to analyze the thermal distribution of transistors and the circuits.

Equivalent small-signal model of InP-based HEMTs with accurate radiation effects characterization

In this paper, an effective equivalent modeling technique has been proposed to describe small-signal characteristics of InP-based high electron mobility transistors (HEMTs) after proton radiation, which is composed of an artificial neural network and equivalent-circuit models. Small-signal intrinsic parameters of InP-based HEMTs are extracted from S-parameters before and after 2 MeV proton radiation as modeling objects. The deep learning model of a generative adversarial network has been explored to expand the measured finite data samples. Four feedforward neural networks are incorporated to equivalent-circuit topology to form the equivalent model, which are trained to accurately predict the radiation-induced variations of Cgs, Cgd, Rds, and gm, respectively. The prediction accuracy of the developed equivalent model has been well verified in terms of the broad-band S-parameters under radiation fluence of 1 × 1014 and 5 × 1013 H+/cm2. This equivalent modeling method with characterization of radiation damage effects could provide significant guidance for the aerospace monolithic millimeter-wave integrated circuit design.

On GaN Low Noise Amplifier: Device Modelling and Circuit Design

The radio frequency spectrum is currently congested due to the advancement in wireless communication systems. For these system, low noise-figure linear amplifier is crucially needed to design the front-end receiver and amplify very low-power received signals without significantly degrading their qualities. Gallium Nitride (GaN) High Electron Mobility Transistor (HEMT) has wider linear dynamic range and thus represents an excellent alternative for designing highly linear Low Noise Power Amplifier (LNA). Also, GaN as a wide bandgap material could be very optimistic to work in harsh and noisy environment such as earth space for satellite communications. In this work, global optimization technique-based noise-models are presented and then used to design LNAs. An extensive review of state-of-the-art GaN HEMT based low noise amplifier is given in this paper. Then different topologies of the low noise amplifier are explored. The techniques of bandwidth enhancement are also reviewed. The design of low noise amplifiers using the developed GaN HEMT model is done at X and K bands of frequencies. The performances of the designed LNAs are compared with state-of-the-art reported LNAs in terms of the Noise Figure (NF), gain and bandwidth. The paper presented very interesting results for the cascade, which exhibited the best NF of 1.6-2 dB and a gain of 14.5-16.4 dB within a bandwidth of 9 to 11 GHz. The highest gain of 25-27 dB was achieved by the quadrature cascode LNA with slightly higher NF of 2.1-2.5 at an operating frequency of 8-12 GHz.

Analysis of Dead-Time Energy Loss in GaN-Based TCM Converters With an Improved GaN HEMT Model

For gallium nitride (GaN) based triangular current mode (TCM) applications, the dead-time has a significant effect on the switching loss. However, previous GaN high electron mobility transistor (HEMT) models focus on the turn- <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">on/off</small> process without fully considering the effect of the dead-time. Hence, this article analyzes the switching transients under the superfluous and insufficient dead-time and evaluates the dead-time loss with an improved GaN HEMT model. The proposed model improves an existing GaN HEMT model by adding the voltage rising/falling time of the gate driver, the dynamic threshold voltage of Schottky-type GaN HEMTs, and an equivalent gate-drain capacitance obtained from the datasheet. Verified by a GaN-based double-pulse test, the proposed model can more accurately calculate the gate-source voltage and the self-commutated reverse conduction voltage. Verified by a GaN-based TCM Buck converter, the proposed model can predict the dead-time loss well and has higher simulation accuracy for the turn- <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">on</small> process induced by the inappropriate dead-time.

Accurate and Effective Nonlinear Behavioral Modeling of a 10-W GaN HEMT Based on LSTM Neural Networks

This paper presents a novel nonlinear behavioral modeling methodology based on long-short-term memory (LSTM) networks for gallium nitride (GaN) high-electron-mobility transistors (HEMTs). There are both theoretical foundations and practical implementations of the modeling procedure provided in this paper. To determine the most appropriate optimizer algorithm for the model presented in this work, four different optimization algorithms are examined. The results of both simulation and experimental validation are provided based on a 10-W GaN HEMT device. According to the developed investigation, the model is capable of extrapolating and interpolating over multiple input power levels and frequencies, including linear, weakly nonlinear, and strongly nonlinear areas. The analysis of the simulated and measured results shows that the developed model has superior performance also when considering the DC drain current ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Ids</i> .). Compared with the existing support vector regression (SVR) based model and the Bayesian based model, the proposed approach shows a significantly improved extrapolation capability.

Electrical Characterization and Modeling of GaN HEMTs at Cryogenic Temperatures

In this work, we present a phenomenological cryogenic model for gallium nitride (GaN) high electron mobility transistors (HEMTs) with validity all the way down to a temperature of 10 K, benchmarked with experimental characterization results. The device under test (DUT) for cryogenic characterization is a GaN HEMT with a channel length of 250 nm and a gate width of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$40~\mu \text{m}$ </tex-math></inline-formula> . The characterization results exhibit the negative threshold voltage shifts of −3.437, −3.087, and −2.998 V at the temperatures of 300, 60, and 10 K, respectively. Additionally, kink effects at cryogenic temperatures in output characteristics are observed that behave non-monotonically with gate-to-source bias. The impact of detrapping is modeled to investigate the negative shift in <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${V}_{\text {TH}}$ </tex-math></inline-formula> with increasing temperature. To model the kink, the effects of temperature, impact ionization, and field-dependent trapping/detrapping on <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${V}_{\text {TH}}$ </tex-math></inline-formula> have been explored and implemented as a submodel in the industry standard Advanced SPICE Model (ASM)-HEMT framework. Here, we aim to overcome the limitations of the prior GaN device models in the quest for enabling GaN-based circuits for cryogenic applications, such as deep space reception, radio astronomy, and quantum computing.

Quasi-2-D Physical Modeling of GaN Microwave HEMTs for RF Applications

The dc and small-signal characterization of microwave gallium nitride (GaN)-based high-electron-mobility transistors (HEMTs) is described, using a new quasi-2-D (Q2D) physical model which allows fast, physics-based electronic and microwave simulation with predictive process variation for these devices at dc and RF frequencies for the first time, which is suitable for device design and development. The predicted results are compared to measured data of transistors intended for communications applications. The simulation uses a self-consistent Schrödinger–Poisson solver, coupled with current- and energy-continuity solutions for carrier transport. The simulator incorporates hot electrons, polarization, temperature dependence, and short-gate effects.

A Difference-Microvariation Solution and Analytical Model for Generic HEMTs

An analytical dc model of AlGaN/GaN and AlGaAs/GaAs-based high-electron mobility transistors (HEMTs) is proposed, while the charge accumulated in the barrier layer at high gate biases voltage is taken into account. To break through the bottleneck problem of solving model accurately and efficiently, an improved difference-microvariation (DM) explicit algorithm is developed to solve the complex transcendental equations of Fermi level and surface potential in the physical model, including two important subbands in a triangular potential well. Compared with the existing analytical surface potential-based algorithms, the DM algorithm quantifies the high-order component and obtains a more precise solution. The universality and accuracy of the model and DM solutions are verified against numerical results and experimental data under a wide range of operation region, which proves that the model combined with DM method is expected to become the suitable simulation tools for generic heterojunction HEMTs.

The Charge-Based Flicker Noise Model for HEMTs

The flicker noise modeling is of great significance in many applications of high electron mobility transistors (HEMTs) in low noise circuits. In this letter, a novel charge-based flicker noise model for HEMTs is proposed, which introduces the trap-charge fluctuation-based flicker noise modeling method to the charge-based MIT virtual source (MVS) HEMT model. This model is highly compatible with the MVS HEMT model. It can predict the flicker noise performance in a physically rigorous and accurate way. This model is verified by the excellent agreement between simulations and measurement results.

An Evolutionary Multilayer Perceptron-Based Large-Signal Model of GaN HEMTs Including Self-Heating and Trapping Effects

Neural networks are widely used to build large-signal models; an appropriate network architecture is important for high model accuracy and good generalization ability. In this article, an evolutionary multilayer perceptron (EMLP)-based modeling approach is proposed to construct an accurate model with a proper architecture for GaN high electron mobility transistors (HEMTs). The multiobjective gray wolf optimizer (MOGWO) is used to optimize architectures, including the number of hidden layers and neurons. The two objective functions consist of the training error, generalization error, number of test cases, and number of parameters. An accurate EMLP-based model with a proper architecture is selected from the Pareto optimal solutions. The proposed method can be directly used to develop a large-signal model considering self-heating and trapping effects. Alternatively, to improve model accuracy and generalization ability, this approach is used to accurately model the effective trap potential and the bias- and temperature-dependent factor. The capacitance models are built with the EMLP and approximation. The large-signal model is implemented in Keysight Advanced Design System (ADS), and a good agreement is achieved between the measured and simulated results.

A Scalable Small-Signal and Noise Model for High-Electron-Mobility Transistors Working Down to Cryogenic Temperatures

This article reports on a scalable, temperature-dependent small-signal and noise model of a 50-nm metamorphic high-electron-mobility transistor (HEMT) technology. The model is valid for temperatures ranging from 5 to 297 K. The highest scalability is achieved by using a distributed model topology. The model is able to predict the small-signal and noise performance of 2-8 finger transistors with absolute gate widths ranging from 10 to 480 μm. Short gate width transistor fingers (5 μm) and wide transistor fingers (100 μm) are covered by the model. The model is valid over a very broad bandwidth from 0.1 to at least 150 GHz. Furthermore, the model covers all reasonable bias points of the given transistor technology. To the best of the authors' knowledge, this is the first scalable HEMT model that is able to predict the small-signal and noise performance at arbitrary cryogenic temperatures. The scaling ratio related to the absolute gate width of the model is the highest among small-signal models reported in the literature.

An efficient drain-lag model for microwave GaN HEMTs based on ASM-HEMT

AbstractLarge-signal modeling of Gallium Nitride (GaN) based high electron mobility transistors (HEMTs) demands a proper description of trapping effects. In this paper, a new, simplified yet accurate drain-lag description is proposed, enhancing the simulation accuracy and the extraction flow of the physics-based compact model ASM-HEMT. The present study investigates the impact of drain lag on specific physical phenomena, focusing on the relation between trap states, surface-potential calculations, and electron transport properties. It is supplemented with a revised extraction procedure, minimizing the required measurements, thereby the undesired consequences of several passes on the same device, using pulsed I-V and pulsed S-parameters only, and approaches for efficient and accurate simulation results. We show that the proposed trap model is a determinative tool for simulating both small and large-signal behavior predicting precisely S-parameters and load-pull performance.

Modeling of Bias-Dependent Effective Velocity and Its Impact on Saturation Transconductance in AlGaN/GaN HEMTs

In this article, we present a surface-potential-based approach to model the bias-dependent effective velocity observed in AlGaN/GaN high-electron-mobility transistors (HEMTs) due to optical phonon scattering. Our model precisely reproduces the progressive decrease in the saturation velocity in GaN HEMTs with increasing gate voltages, as reported in the literature, which is predominantly due to the scattering of electrons, forming the high-density two-dimensional electron gas (2DEG), by optical phonons at high overdrive voltages. We show that this dependence differs from the traditional mobility degradation models in terms of its impact on the device current-voltage (I- V) characteristics and illustrate how the inclusion of a velocity saturation model also provides the model users with an additional handle for parameter extraction. The model is explicit and, by virtue of its Simulation Program with Integrated Circuit Emphasis (SPICE) compatibility, is readily implemented in the industry-standard Advanced SPICE Model for HEMTs (ASM-HEMTs) model and has been validated against experimental dc I-V and RF S-parameter measurements of an in-house GaN device.

Analysis and Modeling of the Temperature-Dependent Nonlinearity of Intrinsic Capacitances in AlGaN/GaN HEMTs

Modeling the temperature-dependent nonlinearity of intrinsic capacitances in AlGaN/GaN high electron mobility transistors (HEMTs) improves model accuracy. In this letter, extraction results indicate that the current modeling methods cannot accurately reflect the variations of nonlinearity in intrinsic capacitances with temperature. This letter analyzes the causes of unmodeled phenomena and characterizes them based on device physics. Verifications show that the improved intrinsic capacitance model in this letter effectively enhances the accuracy of the HEMT model at non-nominal temperatures.

A novel multi-physics field optimization method for GaN HEMT circuit design

A device modeling and topology design method suitable for high-power-density and high-temperature applicationare important to develop with the development of devices. A novel multi-physics analysis model based on GaN high electron mobility transistor (HEMT) is proposed in this paper. The coupled electromagnetic and electrothermal model for GaN HEMT is beneficial to simulate a device’s external characteristic waveform affected by different stray parameters in the surrounding. In addition, the proposed method can accurately reflect the switching loss and transient switching process of GaN HEMT.