All Categories (1-3 of 3)

1. Python-based Toolkit for Solid Solution Strengthening Prediction

   25 Apr 2022 | Contributor(s):: Dongsheng Wen, Michael S Titus

   A python-based tool for prediction solid solution strengthening of complex concentrated alloys using the state-of-the-art models.

2. Module 4: Linear Regression Models

   Online Presentations | 01 Oct 2020 | Contributor(s):: Michael N Sakano, Saaketh Desai, Alejandro Strachan

   This module introduces linear regression in the context of materials science and engineering. We will apply liner regression to predict materials properties and to explore correlations between materials properties via hands-on online simulations. Linear regression is a supervised machine...

3. nanoHUB Materials Simulation Homework: Engineering the Yield Stress of a Material by Controlling Grain Size

   Teaching Materials | 26 Feb 2015 | Contributor(s):: Marisol Koslowski, Tanya Faltens

   This homework assignment uses the nanoplasticity lab simulation tool to enable students to explore how grain size and the competing plastic deformation mechanisms of dislocation motion and grain boundary sliding affect the yield stress of a sample.  Students create conditions that lead to...