
Exploration of the Oxidation Rate of Silicon Wafers via Simulation
04 Nov 2014  Teaching Materials  Contributor(s): Tanya Faltens
This teaching resource is designed for instructors who would like to introduce exploration through simulation into their lessons on silicon oxidation. Stepbystep instructions are provided...
http://nanohub.org/resources/21669

Exploring Thin Film Interference Colors through Simulation
04 Nov 2014  Teaching Materials  Contributor(s): Tanya Faltens
This resource will guide instructors and independent learners through the process of simulating the reflections off of a thin film using the S4: Stanford Stratified Structure Solver simulation...
http://nanohub.org/resources/21667

MOSFET Simulation
04 Oct 2013  Tools  Contributor(s): Chen Shang, Sankarsh Ramadas, Tanya Faltens, derrick kearney, Krishna Madhavan
Displays drain current as a function of sourcedrain voltage for different values of gate voltage, gate dimensions, substrate material, and oxide material in an ntype MOSFET.
http://nanohub.org/resources/mosfetsat

NCN Education Team: Student Research
09 Apr 2014  Online Presentations  Contributor(s): Kelsey Joy Rodgers, Oguz Hanoglu, Yi Kong
http://nanohub.org/resources/20825

Using nanoHUB to Introduce Middle School Students to Models and Simulations
25 Mar 2014  Teaching Materials  Contributor(s): Tanya Faltens
This is a combination handson and simulation activity that will teach middle school students about the function and importance of modeling and simulations in science and engineering while...
http://nanohub.org/resources/20667

Mar 20 2014
Cloudbased, fully interactive simulations via nanoHUB to enhance student learning of materials engineering concepts
Interactive simulations and visualizations enable students to explore abstract concepts in a handson, concrete way. Students can gain familiarity with trends in materials behavior and develop a...
http://nanohub.org/events/details/784

Evaluating the Fermi Function at Ec
09 Mar 2014  Online Presentations  Contributor(s): Tanya Faltens
Short narrated instruction giving stepbystep instructions for evaluating f(E) at Ec. The general method is explained,and a value is calculated for the specific case of Si at 300K.
http://nanohub.org/resources/13912

Evaluating the Fermi Function at Ec + 0.02 eV
15 Oct 2013  Teaching Materials  Contributor(s): Tanya Faltens
This is a short animation explaining how to evaluate the fermi function, given a band diagram and an energy level of interest.
http://nanohub.org/resources/19599

[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)
http://nanohub.org/resources/unisensorydelta

[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)
http://nanohub.org/resources/unisensorybayes

[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)
http://nanohub.org/resources/bisensorybayes

[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)
http://nanohub.org/resources/bisensorydelta

[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
http://nanohub.org/resources/fishbayesrule

[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
http://nanohub.org/resources/fishbackprop

[Illinois]: Sigmoidal unit training with the delta rule
26 Jun 2013  Tools  Contributor(s): Lisa Sproat, NanoBio Node, Jessica S Johnson
Uses the delta rule to train a single sigmoidal unit with feedback to simulate the responses of neurons in the parabigeminal nucleus
http://nanohub.org/resources/pbndeltarule

[Illinois]: Predictorcorrector simulation of parabigeminal nucleus neural responses
24 Jun 2013  Tools  Contributor(s): Lisa Sproat, NanoBio Node, Jessica S Johnson
Implements a predictorcorrector simulation of the responses of neurons in the parabigeminal nucleus
http://nanohub.org/resources/pbnpredict

[Illinois]: Midbrain dopamine neuron responses to temporaldifference learning
21 Jun 2013  Tools  Contributor(s): Lisa Sproat, Jessica S Johnson, NanoBio Node
Simulates the responses of midbrain dopamine neurons using temporal difference learning
http://nanohub.org/resources/midbraindopamin

Locustflight central pattern generator
06 Jun 2013  Tools  Contributor(s): Lisa L Sproat, NanoBio Node, Jessica S Johnson
Implements a linear version of Wilson's model of the locustflight central pattern generator
http://nanohub.org/resources/wilsoncpg

[Illinois]: Two leaky integrators in series
31 May 2013  Tools  Contributor(s): Lisa L Sproat, John Feser, Jessica S Johnson, NanoBio Node
Implements a model having two units (leaky integrators) in series, each with recurrent, excitatory selfconnections allowing the units to exert positive feedback on themselves
http://nanohub.org/resources/twoleakseries

Unit Cell Ranking Tasks
15 Oct 2012  Teaching Materials  Contributor(s): Tanya Faltens
This set of ranking tasks is designed to help the learner work with and understand some of the features of common structures: planar densities, atomic densities, atomic packing factor and...
http://nanohub.org/resources/15427