A Coupled Schrödinger Drift-Diffusion Model for Quantum Semiconductor Device Simulations

2002 ◽  
Vol 181 (1) ◽  
pp. 222-259 ◽  
Author(s):  
P. Degond ◽  
A. El Ayyadi
Keyword(s):  
Diffusion Model ◽  
Semiconductor Device ◽  
Drift Diffusion Model ◽  
Drift Diffusion ◽  
Quantum Semiconductor

scholarly journals Additive Decomposition Applied to the Semiconductor Drift-Diffusion Model

VLSI Design ◽  
1998 ◽  
Vol 8 (1-4) ◽  
pp. 393-399
Author(s):  
Elizabeth J. Brauer ◽  
Marek Turowski ◽  
James M. McDonough
Keyword(s):  
Diffusion Model ◽  
Large Scale ◽  
Semiconductor Device ◽  
Stokes Equations ◽  
Numerical Technique ◽  
Small Scale ◽  
Drift Diffusion Model ◽  
Drift Diffusion ◽  
Additive Decomposition ◽  
Scale Grid

A new numerical method for semiconductor device simulation is presented. The additive decomposition method has been successfully applied to Burgers' and Navier-Stokes equations governing turbulent fluid flow by decomposing the equations into large-scale and small-scale parts without averaging. The additive decomposition (AD) technique is well suited to problems with a large range of time and/or space scales, for example, thermal-electrical simulation of power semiconductor devices with large physical size. Furthermore, AD adds a level of parallelization for improved computational efficiency. The new numerical technique has been tested on the 1-D drift-diffusion model of a p-i-n diode for reverse and forward biases. Distributions of φ, n and p have been calculated using the AD method on a coarse large-scale grid and then in parallel small-scale grid sections. The AD results agreed well with the results obtained with a traditional one-grid approach, while potentially reducing memory requirements with the new method.

Error analysis of drift-diffusion model of semiconductor device numerical simulation

2014 ◽  
Vol 26 (6) ◽  
pp. 63204
Author(s):  
李勇 Li Yong ◽  
贡顶 Gong Ding ◽  
宣春 Xuan Chun ◽  
夏洪富 Xia Hongfu ◽  
谢海燕 Xie Haiyan ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Error Analysis ◽  
Diffusion Model ◽  
Semiconductor Device ◽  
Drift Diffusion Model ◽  
Drift Diffusion

Multicomponent Model of Charge Transport in Quantum Semiconductor Devices

2021 ◽  
Vol 23 (1) ◽  
pp. 24-31
Author(s):  
I.A. Obukhov ◽  
Keyword(s):  
Charge Transport ◽  
Diffusion Model ◽  
Semiconductor Devices ◽  
Optoelectronic Devices ◽  
Drift Diffusion Model ◽  
Drift Diffusion ◽  
Classical Approximation ◽  
Quasi Classical Approximation ◽  
Quantum Semiconductor ◽  
Multicomponent Model

A model that allows taking into account the influence of quantum and non-equilibrium effects to the characteristics of semiconductor devices is presented. The model was successfully used for calculation the characteristics of resonant-tun-neling diodes, electronic, thermionic and optoelectronic devices based on nanowires. In a quasi-classical approximation it goes into a drift-diffusion model.

scholarly journals Informing cognitive abstractions through neuroimaging: The neural drift diffusion model.

2015 ◽  
Vol 122 (2) ◽  
pp. 312-336 ◽  
Author(s):  
Brandon M. Turner ◽  
Leendert van Maanen ◽  
Birte U. Forstmann
Keyword(s):  
Diffusion Model ◽  
Drift Diffusion Model ◽  
Drift Diffusion

Incorporating photon recycling into the analytical drift-diffusion model of high efficiency solar cells

2014 ◽  
Vol 116 (19) ◽  
pp. 194504 ◽  
Author(s):  
Matthew P. Lumb ◽  
Myles A. Steiner ◽  
John F. Geisz ◽  
Robert J. Walters
Keyword(s):  
Solar Cells ◽  
Diffusion Model ◽  
High Efficiency ◽  
Drift Diffusion Model ◽  
Drift Diffusion ◽  
High Efficiency Solar Cells ◽  
Photon Recycling
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