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

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.

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 ◽  
...  

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

2014 ◽  
Vol 116 (19) ◽  
pp. 194504 ◽  
Author(s):  
Matthew P. Lumb ◽  
Myles A. Steiner ◽  
John F. Geisz ◽  
Robert J. Walters

2022 ◽  
Vol 15 ◽  
Author(s):  
Ankur Gupta ◽  
Rohini Bansal ◽  
Hany Alashwal ◽  
Anil Safak Kacar ◽  
Fuat Balci ◽  
...  

Many studies on the drift-diffusion model (DDM) explain decision-making based on a unified analysis of both accuracy and response times. This review provides an in-depth account of the recent advances in DDM research which ground different DDM parameters on several brain areas, including the cortex and basal ganglia. Furthermore, we discuss the changes in DDM parameters due to structural and functional impairments in several clinical disorders, including Parkinson's disease, Attention Deficit Hyperactivity Disorder (ADHD), Autism Spectrum Disorders, Obsessive-Compulsive Disorder (OCD), and schizophrenia. This review thus uses DDM to provide a theoretical understanding of different brain disorders.


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