Tags: NCN Group - Materials Science

Description

Education group: Materials Science.

Materials Science.

Resources (1-20 of 147)

  1. MIT Atomic-Scale Modeling Toolkit

    Tools | 15 Jan 2008 | Contributor(s):: David A Strubbe, Enrique Guerrero, daniel richards, Elif Ertekin, Jeffrey C Grossman, Justin Riley

    Tools for Atomic-Scale Modeling

  2. MATE 370 Virtual Lab: Exploring Phase Transformations Through nanoHUB Nanomaterial Mechanics Explorer Tool

    Teaching Materials | 24 Sep 2020 | Contributor(s):: Mohsen B Kivy, Crystal Ipong

    This lab explores the kinetics of phase transformation using nanoHUB tools.

  3. MATE 370 Virtual Lab: Exploring Nucleation, Crystallization, and Growth through nanoHUB Virtual Kinetics Tools

    Teaching Materials | 24 Sep 2020 | Contributor(s):: Mohsen B Kivy, Crystal Ipong

    This lab explores the kinetics of nucleation, crystallization, and growth processes using nanoHUB tools.

  4. MATE 370 Virtual Lab: Exploring Diffusion through nanoHUB Defect- coupled and Concentration-dependent Diffusion Tools

    Teaching Materials | 24 Sep 2020 | Contributor(s):: Mohsen B Kivy, Crystal Ipong

    This lab explores the kinetics of solid-state diffusion using nanoHUB tools.

  5. Linear Regression Young's modulus

    Tools | 16 Sep 2020 | Contributor(s):: Michael N Sakano, Saaketh Desai, Alejandro Strachan

    Use linear regression to extract Young's modulus and yield stress from stress-strain data

  6. Materials Science Education Champion Seminar Series

    Series | 14 Aug 2020 | Contributor(s):: Susan P Gentry

    This webinar series will highlight computer simulation modules that are used by MSE educators around the country. Each topical webinar will feature a presentation by MSE faculty that use the tools as well as time for group discussion.

  7. Computational Labs in Kinetics of Materials and Process Design (California Polytechnic State University)

    Series | 07 Sep 2020 | Contributor(s):: Mohsen B Kivy, Crystal Ipong

    Kinetics of Materials and Process Design (MATE 370) is a 4-unit major course for junior-year undergraduate students of the Materials Engineering Department, Cal Poly State University. The Materials Engineering Department endorses the applications of theory to practice through its...

  8. Illustrative Mathematical Concepts

    Tools | 29 Jul 2020 | Contributor(s):: Hae Ji Kwon, Mike Jovanovich, David R. Ely

    Illustrates mathematical concepts and their applications

  9. Interactive Learning Tools for Scientific Computing and Data Analysis Using R

    Tools | 29 Jul 2020 | Contributor(s):: Cindy Nguyen, Rei Sanchez-Arias

    Root-finding methods and numerical optimization techniques with applications in science, engineering, and data analysis

  10. Data Analysis of Normal Data Sets in Engineering

    Tools | 24 Jul 2020 | Contributor(s):: Joseph Joshua Williams, Nancy Ruzycki

    Statistical and data analysis concepts in engineering

  11. Matlab Data Analysis Using Jupyter Notebooks

    Tools | 24 Jul 2020 | Contributor(s):: Jon Nykiel, Anna Leichty, Zachary D McClure, Alejandro Strachan, Aileen Ryan, Adrian Nat Gentry, Amanda Johnston, Tamara Jo Moore, Allen Garner, Peter Bermel

    Use Jupyter Notebooks with a Matlab kernel running in the background for data analysis and intro to engineering homework problems

  12. Materials Camp for High School Students

    Series | 01 Jul 2020 | Contributor(s):: Amber Genau

    These activities were all developed for the Materials Camp program at the University of Alabama at Birmingham (UAB), which began in 2011. The camp is a five-day, non-residential program designed to introduce mostly local 10th-12th grade students to the field of materials engineering and the...

  13. Balloon Skewer Relay Race

    Teaching Materials | 29 Jun 2020 | Contributor(s):: Amber Genau

    Do you think you could get a bamboo barbecue skewer through a balloon without popping it?  With a little dish soap and some practice, I bet you could!  Skewering a balloon is a fun and inexpensive way to demonstrate the structure-dependent properties of polymers. Polymers are made...

  14. Materials Matching Mixer Activity

    Teaching Materials | 29 Jun 2020 | Contributor(s):: Amber Genau

    This materials-themed ice breaker activity is great for the first day of a camp program to get students thinking about basic material properties, as well as talking to each other and speaking out loud in front of the group.  The name of a common engineering material (steel, rubber, concrete,...

  15. Pineapple Packaging Design Challenge

    Teaching Materials | 29 Jun 2020 | Contributor(s):: Amber Genau

    This activity asks students to work in teams to consider the pros and cons of different materials as a container for cut pineapple (metal can plastic jar, glass jar).  It reinforces the differences between different categories of material, weighing conflicting factors to reach a design...

  16. Engineering Communication with Tinker Toys

    Teaching Materials | 29 Jun 2020 | Contributor(s):: Amber Genau

    This resource describes three variations on an engineering communication activity using Tinker Toys.  In the main activity, small groups of students are given a bag of Tinker Toys and instructed to build anything they like.  They are then asked to write down building instructions for...

  17. Machine Learning Lab Module

    Tools | 12 Jun 2020 | Contributor(s):: BENJAMIN AFFLERBACH, Rundong Jiang, Josh Tappan, DANE MORGAN

    A lab activity for introduction to machine learning in materials science

  18. Machine Learning Workshop for Materials Science

    Workshops | 27 Jan 2020 | Contributor(s):: Saaketh Desai

    This workshop covers the fundamentals of machine learning and data science, with a focus on material science applications. This workshop includes a hands-on demonstration of the nanoHUB tool Machine Learning for Materials Science: Part 1.

  19. MSEML: Machine Learning for Materials Science Tool on nanoHUB

    Online Presentations | 27 Jan 2020 | Contributor(s):: Saaketh Desai

    This talk is a hands-on demonstration using the nanoHUB tool Machine Learning for Materials Science: Part 1.

  20. Data Science and Machine Learning for Materials Science

    Online Presentations | 22 Jan 2020 | Contributor(s):: Saaketh Desai

    This talk covers the fundamentals of machine learning and data science, focusing on material science applications. The talk is for a general audience, attempting to introduce basic concepts such as linear regression, supervised learning with neural networks including forward and back...