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Monte Carlo methods are a class of computational algorithms that rely on repeated random sampling to compute their results. Monte Carlo methods are often used in simulating physical and mathematical systems. Because of their reliance on repeated computation of random or pseudo-random numbers, these methods are most suited to calculation by a computer and tend to be used when it is unfeasible or impossible to compute an exact result with a deterministic algorithm.
Learn more about quantum dots from the many resources on this site, listed below. More information on Monte Carlo method can be found here.
ECE 695A Lecture 14a: Voltage Dependent HCI I
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19 Feb 2013 | Online Presentations | Contributor(s): Muhammad Alam
Outline: Background and Empirical Observations Theory of Hot Carriers: Hydrodynamic Model Theory of Hot Carriers: Monte Carlo Model Theory of Hot Carriers: Universal Scaling Conclusion …
ECE 695A Lecture 14b: Voltage Dependent HCI II
[Illinois]: CSE Seminar Series: Advances in First-principles Computational Materials Science
20 Nov 2012 | Online Presentations | Contributor(s): Elif Ertekin
The capability to rationally design new materials with tailored properties and functionality on a computer remains a grand challenge whose success would have tremendous impact on several …
Particle Simulations of Ion Generation and Transport in Microelectromechanical Systems and Micropropulsion
29 May 2012 | Online Presentations | Contributor(s): Venkattraman Ayyaswamy
The first part of the talk deals with use of the PIC method with Monte Carlo collisions (MCC) between electrons and the ambient neutral gas to develop models to predict charge accumulation, breakdown …
ECE 656 Lecture 41: Transport in a Nutshell
21 Feb 2012 | Online Presentations | Contributor(s): Mark Lundstrom
ECE 656 Lecture 34a: Monte Carlo Simulation I
Outline Introduction Review of carrier scattering Simulating carrier trajectories Free flight Collision Update after collision Putting it all together Summary
ECE 656 Lecture 34b: Monte Carlo Simulation II
ECE 656 Lecture 32: Balance Equation Approach III
19 Jan 2012 | Online Presentations | Contributor(s): Mark Lundstrom
Outline: Review of L31 Carrier temperature and heat flux Heterostructures Summary
Discussion about Ion Channels Using Reduced Model Approaches
21 Sep 2011 | Online Presentations | Contributor(s): James Fonseca
The seminar will cover the reasons how the channels are able to selectively permit the flow of certain species of ions while blocking other physiological cations.
ECE 656 Lecture 31: Monte Carlo Simulation
01 Dec 2009 | Online Presentations | Contributor(s): Mark Lundstrom
Outline: Introduction Review of carrier scattering Simulating carrier trajectories Free flight Collision Update after collision Putting it all together Summary
ECE 656 Lecture 30: Balance Equation Approach III
Outline Carrier Temperature and Heat Flux Balance equations in 3D Heterostructures Summary
Illinois PHYS 466, Lecture 18: Kinetic Monte Carlo (KMC)
04 May 2009 | Online Presentations | Contributor(s): David M. Ceperley, Omar N Sobh
Quantum and Thermal Effects in Nanoscale Devices
18 Sep 2008 | Online Presentations | Contributor(s): Dragica Vasileska
To investigate lattice heating within a Monte Carlo device simulation framework, we simultaneously solve the Boltzmann transport equation for the electrons, the 2D Poisson equation to get the …
Molecular modeling of lipid bilayer edge and hybrid-MCMD method: Implementation and application
29 Apr 2008 | Online Presentations | Contributor(s): Yong Jiang
Introduction to mixed lipid systems, Hybrid Monte Carlo and MD (atomistic) algorithm for mixed lipid systems
Practical Introduction to the BioMOCA Suite
23 Apr 2008 | Online Presentations | Contributor(s): David Papke
In this presentation, I describe how to use the online BioMOCA Suite. I explain how to prepare the .pqr input protein structure from a .pdb structure. I then explain in detail how to use each of the …
Materials Science on the Atomic Scale with the 3-D Atom Probe
08 Nov 2006 | Online Presentations | Contributor(s): George D. W. Smith
Some of the key goals of materials science and technology are to be able to design a material from first principles, to predict its behaviour, and also to optimise the processing route for its …
Review of Several Quantum Solvers and Applications
11 Jun 2004 | Online Presentations | Contributor(s): Umberto Ravaioli
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