Comparison of drift–diffusion model and hydrodynamic carrier transport model for simulation of GaN-based IMPATT diodes

This paper presents a numerical simulation of a Wurtzite-GaN-based IMPATT diode operating at the low-end frequency of terahertz range. Conventional classical drift–diffusion model is independent of the energy relaxation effect at high electric field. However, in this paper, a hydrodynamic carrier transport model including a new energy-based impact ionization model is used to investigate the dc and high-frequency characteristics of an IMPATT diode with a traditional drift–diffusion model as comparison. Simulation results show that the maximum rf power density and the dc-to-rf conversion efficiency are larger for conventional drift–diffusion model because it overestimates the impact ionization rate. Through hydrodynamic simulation we revealed that the impact ionization rates are seriously affected by the high and rapidly varied electric field and the electron energy relaxation effect, which lead to the rf output power density and the dc-to-rf conversion efficiency falls gradually, and a wider operation frequency band is obtained compared with the drift–diffusion model simulation at frequencies over 310 GHz.

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An Application-Driven Improvement of the Drift–Diffusion Model for Carrier Transport in Decanano-Scaled CMOS Devices

IEEE Transactions on Electron Devices ◽

10.1109/ted.2008.2004474 ◽

2008 ◽

Vol 55 (11) ◽

pp. 3227-3235 ◽

Cited By ~ 5

Author(s):

Christian Kampen ◽

Alexander Burenkov ◽

JÜrgen Lorenz ◽

Heiner Ryssel ◽

ValÉrie Aubry-Fortuna ◽

...

Keyword(s):

Diffusion Model ◽

Carrier Transport ◽

Drift Diffusion Model ◽

Drift Diffusion ◽

Scaled Cmos

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Simulation of Carrier Transport across Heterojunctions Based on Drift-Diffusion Model Incorporating an Effective Potential

Japanese Journal of Applied Physics ◽

10.1143/jjap.41.l1306 ◽

2002 ◽

Vol 41 (Part 2, No. 11B) ◽

pp. L1306-L1308 ◽

Cited By ~ 4

Author(s):

Eiichi Sano

Keyword(s):

Diffusion Model ◽

Effective Potential ◽

Carrier Transport ◽

Drift Diffusion Model ◽

Drift Diffusion

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Simultaneous Hierarchical Bayesian Parameter Estimation for Reinforcement Learning and Drift Diffusion Models: a Tutorial and Links to Neural Data

Computational Brain & Behavior ◽

10.1007/s42113-020-00084-w ◽

2020 ◽

Vol 3 (4) ◽

pp. 458-471 ◽

Cited By ~ 3

Author(s):

Mads L. Pedersen ◽

Michael J. Frank

Keyword(s):

Parameter Estimation ◽

Reinforcement Learning ◽

Diffusion Model ◽

Simultaneous Estimation ◽

Model Parameters ◽

Hierarchical Bayesian ◽

Drift Diffusion Model ◽

Drift Diffusion ◽

Bayesian Parameter Estimation ◽

The Impact

AbstractCognitive models have been instrumental for generating insights into the brain processes underlying learning and decision making. In reinforcement learning it has recently been shown that not only choice proportions but also their latency distributions can be well captured when the choice function is replaced with a sequential sampling model such as the drift diffusion model. Hierarchical Bayesian parameter estimation further enhances the identifiability of distinct learning and choice parameters. One caveat is that these models can be time-consuming to build, sample from, and validate, especially when models include links between neural activations and model parameters. Here we describe a novel extension to the widely used hierarchical drift diffusion model (HDDM) toolbox, which facilitates flexible construction, estimation, and evaluation of the reinforcement learning drift diffusion model (RLDDM) using hierarchical Bayesian methods. We describe the types of experiments most applicable to the model and provide a tutorial to illustrate how to perform quantitative data analysis and model evaluation. Parameter recovery confirmed that the method can reliably estimate parameters with varying numbers of synthetic subjects and trials. We also show that the simultaneous estimation of learning and choice parameters can improve the sensitivity to detect brain–behavioral relationships, including the impact of learned values and fronto-basal ganglia activity patterns on dynamic decision parameters.

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Comprehensive Study of the Electrothermal Operation of SiC Power Devices Using a Fully Coupled Physical Transport Model

MRS Proceedings ◽

10.1557/proc-622-t1.5.1 ◽

2000 ◽

Vol 622 ◽

Author(s):

M. Lades ◽

W. Kaindl ◽

G. Wachutka

Keyword(s):

Transport Theory ◽

Impact Ionization ◽

Transport Model ◽

Drift Diffusion Model ◽

Power Devices ◽

Drift Diffusion ◽

Material Parameters ◽

Numerical Studies ◽

Fully Coupled ◽

Comprehensive Study

ABSTRACTBased on an extended electrothermal drift-diffusion model formulated within the framework of phenomenological transport theory, a consistent set of material parameters for 4H- and 6H-SiC is presented. Furthermore we report on detailed numerical studies of the coupled effect between transient impurity kinetics and impact ionization, which alters the reverse blocking characteristics of power devices under short switching conditions.

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Non Local Impact Ionization Effects in Semiconductor Devices

VLSI Design ◽

10.1155/1998/72767 ◽

1998 ◽

Vol 6 (1-4) ◽

pp. 291-297 ◽

Cited By ~ 1

Author(s):

Duilio Meglio ◽

Corrado Cianci ◽

Aldo Di Carlo ◽

Paolo Lugli

Keyword(s):

Carrier Transport ◽

Impact Ionization ◽

Semiconductor Devices ◽

High Energy ◽

Drift Diffusion ◽

Non Local ◽

Local Impact ◽

Ionization Coefficients ◽

The Impact ◽

Space Effects

Impact ionization processes define the breakdown characteristics of semiconductor devices. An accurate description of such phenomenon, however, is limited to very sophisticated device simulators such as Monte Carlo. A new physical model for the impact ionization process is presented, which accounts for dead space effects and high energy carrier transport at a Drift Diffusion level. Such model allows to define universal impact ionization coefficients which are device-geometry independent. By using available experimental data these parameters have been calculated for In0.53Ga0.47As.

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Carrier Transport Properties of GAN in High Electric Field

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.c1017.1083s19 ◽

2019 ◽

Vol 8 (3S) ◽

pp. 88-93

Keyword(s):

Electric Field ◽

Transport Properties ◽

Carrier Transport ◽

Impact Ionization ◽

Maximum Velocity ◽

Ionization Rate ◽

High Electric Field ◽

Electric Field Increase ◽

Valence Bands ◽

The Impact

The Monte Carlo (MC) simulation of the carrier transport mechanisms including impact ionization at high electric field in GaN is presented. Two non-parabolic conduction and valence bands were considered for the simulation of transport properties of electron and hole respectively. The carriers’ drift velocity and energy are simulated as a function of applied electric field at room temperature. The maximum velocity of electron is 2.85 × 107 cm/s at 140 kV/cm. The velocity of electron is saturated at 2 × 107 cm/s at electric field greater than 300 kV/cm. In our work, the velocity of hole is 5 × 106 cm/s at 500 kV/cm. Electron energy increases as the electric field increase and fluctuated at electric field greater than 600 kV/cm when impact ionization occurred. The impact ionization rates are obtained by using modified Keldysh equation. The hole impact ionization rate is higher than that of electron. This work also shows higher electron impact ionization coefficient than that of hole at electric field greater than 4.04 MV/cm

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