
Physics and Simulation of Nanoscale Electronic and Thermoelectric Devices
28 Jun 2013  Papers  Contributor(s): raseong kim
For the past few decades, transistors have been continuously scaled. Dimensions are now at the nanoscale, and device performance has dramatically improved. Nanotechnology is also achieving breakthroughs in thermoelectrics, which have suffered from low efficiencies for decades. As the device...

IIIV Nanoscale MOSFETS: Physics, Modeling, and Design
28 Jun 2013  Papers  Contributor(s): Yang Liu
As predicted by the International Roadmap for Semiconductors (ITRS), power consumption has been the bottleneck for future silicon CMOS technology scaling. To circumvent this limit, researchers are investigating alternative structures and materials, among which IIIV compound semiconductorbased...

[Illinois]: Avoidance Learn Simulation with 'Call' Neuron
25 Jun 2013  Tools  Contributor(s): AbderRahman N Sobh, NanoBio Node, Jessica S Johnson
This script simulates avoidance learning as a reinforcement learning with two upper motoneurons (sumo and fumo) and one "call" neuron.

Semiconductor Device Fundamentals Testbook Module B: Diode Basics
01 Jul 2013  Teaching Materials  Contributor(s): Robert F. Pierret
This is module B (part 2) of the Testbook for Semiconductor Device Fundamentals.

Device Physics and Simulation of Silicon Nanowire Transistors
28 Jun 2013  Papers  Contributor(s): Jing Wang
As the conventional silicon metaloxidesemiconductor fieldeffect transistor (MOSFET) approaches its scaling limits, many novel device structures are being extensively explored. Among them, the silicon nanowire transistor (SNWT) has attracted broad attention from both the semiconductor industry...

Carbon Nanotube Electronics: Modeling, Physics, and Applications
28 Jun 2013  Papers  Contributor(s): Jing Guo
In recent years, significant progress in understanding the physics of carbon nanotube electronic devices and in identifying potential applications has occurred. In a nanotube, low bias transport can be nearly ballistic across distances of several hundred nanometers. Deposition of highk gate...

Modeling Quantum Transport i Nanoscale Transistors
28 Jun 2013  Papers  Contributor(s): Ramesh Venugopal
As critical transistor dimensions scale below the 100 nm (nanoscale) regime, quantum mechanical effects begin to manifest themselves and affect important device performance metrics. Therefore, simulation tools which can be applied to design nanoscale transistors in the future, require new theory...

Physics and Simulation of QuasiBallistic Transport in Nanoscale Transistors
28 Jun 2013  Papers  Contributor(s): JungHoon Rhew
The formidable progress in microelectronics in the last decade has pushed thechannel length of MOSFETs into decanano scale and the speed of BJTs into hundreds of gigahertz. This progress imposes new challenges on device simulation as the essential physics of carrier transport departs that of...

Nanoscale MOSFETS: Physics, Simulation and Design
28 Jun 2013  Papers  Contributor(s): Zhibin Ren
This thesis discusses device physics, modeling and design issues of nanoscale transistors at the quantum level. The principle topics addressed in this report are 1) an implementation of appropriate physics and methodology in device modeling, 2)development of a new TCAD (technology computer aided...

TwoDimensional Scattering Matrix Simulations of Si MOSFET'S
28 Jun 2013  Papers  Contributor(s): Carl R. Huster
For many years now, solid state device simulators have been based on the driftdiffusion equations. As transistor sizes have been reduced, there has been considerable concern about the predictive capability of these simulators. This concern has lead to the development of a number of simulation...

Direct Solution of the Boltzmann Transport Equation in Nanoscale Si Devices
28 Jun 2013  Papers  Contributor(s): Kausar Banoo
Predictive semiconductor device simulation faces a challenge these days. As devices are scaled to nanoscale lengths, the collisiondominated transport equations used in current device simulators can no longer be applied. On the other hand, the use of a better, more accurate Boltzmann Transport...

Computational and Experimental Study of Transport in Advanced Silicon Devices
28 Jun 2013  Papers  Contributor(s): Farzin Assad
In this thesis, we study electron transport in advanced silicon devices by focusing on the two most important classes of devices: the bipolar junction transistor (BJT) and the MOSFET. In regards to the BJT, we will compare and assess the solutions of a physically detailed microscopic model to...

[Illinois]: Fish classification using backpropagation
28 Jun 2013  Tools  Contributor(s): Lisa Sproat, Jessica S Johnson, NanoBio Node
Trains a threelayered network of sigmoidal units using backpropagation to classify fish according to their lengths

[Illinois]: Posterior probabilities of hypothetical fish classes
28 Jun 2013  Tools  Contributor(s): Lisa Sproat, Jessica S Johnson, NanoBio Node
Computes the posterior probabilities of each of three hypothetical fish classes using Bayes' rule

[Illinois]: Posterior probability of a target given singlesensory input (Bayes')
28 Jun 2013  Tools  Contributor(s): Lisa Sproat, Jessica S Johnson, NanoBio Node
Computes the posterior probability of a target given sensory input of one modality (i.e., visual)

[Illinois]: Posterior target probability given singlesensory input (delta rule)
28 Jun 2013  Tools  Contributor(s): Lisa Sproat, Jessica S Johnson, NanoBio Node
Trains a single sigmoidal unit using the delta rule to estimate posterior target probability given sensory input of one modality (i.e., visual)

[Illinois]: Posterior probability of a target given input for two senses (Bayes')
28 Jun 2013  Tools  Contributor(s): Lisa Sproat, Jessica S Johnson, NanoBio Node
Computes the posterior probability of a target given sensory input of two modalities (i.e., visual and auditory)

[Illinois]: Posterior probability of a target given input for two senses (delta)
28 Jun 2013  Tools  Contributor(s): Lisa Sproat, Jessica S Johnson, NanoBio Node
Trains a single sigmoidal unit using the delta rule to estimate posterior target probability given sensory input of two modalities (i.e., visual and auditory)

[Illinois]: Error Gradient Estimations Due to Perturbation of One Weight at a Time
29 Jun 2013  Tools  Contributor(s): AbderRahman N Sobh, Jessica S Johnson, NanoBio Node
This tool trains twolayered networks of sigmoidal units to associate patterns using perturbation of one weight at a time.

Microbeam Dynamics with Varying Force Model
01 Jul 2013  Tools  Contributor(s): Saagar Unadkat
Simulate the dynamics of microbeams with Knudsen Forces, Electrostatic and GForces.