nanoHUB-U: From Atoms to Materials: Predictive Theory and Simulations
MSE 270: Atomistic Materials Science
EAFIT-Purdue: online simulations in engineering and science education
Atomistic View of Materials: Modeling & Simulation
Introduction to Uncertainty Quantification
Introduction to Heterogeneous Integration and Electronics Packaging
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SimTools: Delivering Simulations in the Era of Abundant Data
04 Jun 2021 | Online Presentations | Contributor(s): Alejandro Strachan
This presentation introduces SimTool, a library that allows developers to create, publish, and share reproducible workflows with well-defined and verified inputs and outputs.
Active learning challenge for optimal material properties
08 Apr 2021 | Tools | Contributor(s): Zachary D McClure, Alejandro Strachan
Explore active learning methods to search known and unknown spaces of alloys and their material hardness
nanoHUB R&D 100 Award Submission Video
05 Mar 2021 | Online Presentations | Contributor(s): Gerhard Klimeck, Alejandro Strachan
We at nanoHUB would like to thank our users and content contributors as well as our partners at Purdue University and elsewhere around the globe for all the support they have given us over the years. We couldn’t have done it without you.Purdue University nanoHUB.org, a web platform for...
Thermo-Calc Educational Package
23 Mar 2021 | Tools | Contributor(s): Paul Mason, Alejandro Strachan
Thermo-Calc Educational Package
Module 3: Materials Descriptors for Data Science
27 Jan 2021 | Online Presentations | Contributor(s): Alejandro Strachan, Juan Carlos Verduzco Gastelum, Zachary D McClure
This module focuses on the use of descriptors to improve the description of materials in machine learning. Augmenting input parameters with appropriate descriptors (a process sometimes called featurization) can often significantly improve the accuracy of predictive models. Ideal descriptors are...
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Purdue Workshop—Predictive materials modeling and simulations: nano- and micro-mechanics
This by-invitation-only workshop will focus on recent progress and current challenges in the area of experimentally validated, predictive modeling of mechanical properties of nano- or micro-engineered materials. Areas of interest include micro- and nano-electromechanical devices...
Learning Module: Atomic Picture of Plastic Deformation in Metals
The main goal of this learning module is to introduce students to the atomic-level processes responsible for plastic deformation in crystalline metals and help them develop a more intuitive understanding of how materials work at molecular scales. Image to the right shows plastic deformation of a...
Molecular dynamics simulations of materials
What is MD?
Molecular dynamics involves the numerical solution of the classical equations of motion (F=ma) for every single atom in material. The result is a very detailed description of the temporal evolution of the material: we obtain the position, velocity and force of every atom as a...
Resources for Materials Science and Engineering
Ab initio electronic structure simulation tools
:ABINIT is a package whose main program allows to find the total energy, charge density and electronic structure of systems made of electrons and nuclei (molecules and periodic solids) within Density Functional Theory, using...
Learning Module: Bonding and Band Structure in Silicon
The main goal of this learning module is to help students learn about the correlation between atomic structure and electronic properties, and help them develop a more intuitive understanding of the origin of electronic bands in a material via hand-on exploration using online electronic structure...
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