All Categories (1-20 of 181)

1. 1D finite element analysis ME 323

   Tools | 19 Mar 2018 | Contributor(s):: Peter Kolis, Marisol Koslowski

   Mechanics of Materials using Jupyter Notebooks

2. A Guided Tour of Interactive Jupyter Notebooks Powered by nanoHUB

   Online Presentations | 20 Feb 2023 | Contributor(s):: Daniel Mejia

   In this presentation, we will take you on a guided tour of interactive Jupyter Notebooks powered by nanoHUB. Jupyter is a powerful tool for data science and scientific computing that provides an intuitive interface for a variety of programming languages; Jupyter in nanoHUB provides even more...

3. A virion endocytosis tissue simulator

   Tools | 13 Apr 2020 | Contributor(s):: Yafei Wang, Randy Heiland, Paul Macklin

   Simulate virus endocytosis (internalization), ACE2 receptor dynamics with PhysiCell

4. A virion infected-cell response tissue simulator

   Tools | 13 Apr 2020 | Contributor(s):: Yafei Wang, Randy Heiland, Paul Macklin

   Simulate infected cell response to virus with PhysiCell

5. A virion replication tissue simulator

   Tools | 13 Apr 2020 | Contributor(s):: Yafei Wang, Randy Heiland, Paul Macklin

   Simulate virus replication dynamics with PhysiCell

6. AAE 33301 Fluid Mechanics Lab Purdue AeroAstro

   Tools | 19 Oct 2023 | Contributor(s):: Sally Bane, Adarsh Agrawal

   Jupyter notebook intended for students in Purdue AeroAstro to carry out data recording and analysis during Fluid Mechanics lab execution.

7. AMIGOS - Hypoxia

   Tools | 25 Apr 2019 | Contributor(s):: Furkan Kurtoglu, John Metzcar, Kali Nicole Konstantinopoulos, Timothy M Mahajan, Randy Heiland, Paul Macklin

   Modeling Tumor in Hypoxic Condition

8. Atomistic Polymer Workflow Notebook

   Tools | 19 Oct 2017 | Contributor(s):: Benjamin P Haley

   Run PolymerModeler and nuSIMM tools to create atomistic polymer systems

9. Autonomous Neutron Diffraction Explorer

   Tools | 01 Nov 2021 | Contributor(s):: Austin McDannald

   Autonomously control neutron diffraction experiments to discover order parameter.

10. Bayesian optimization tutorial using Jupyter notebook

    Tools | 11 Jun 2021 | Contributor(s):: Hieu Doan, Garvit Agarwal

    Active learning via Bayesian optimization for materials discovery

11. Blockchain & Proof of Useful Work

    Online Presentations | 01 Jul 2022 | Contributor(s):: Alejandro Strachan, Oneal Douglin, Yu-Chung Chang, Alfonso Daniel Meraz, Brian Hyun-jong Lee, Shivam Tripathi, The Micro Nano Technology - Education Center

12. Blockchain and proof of work lab

    Tools | 16 Dec 2021 | Contributor(s):: Oneal Douglin, Yu-Chung Chang, Alfonso Daniel Meraz, Shivam Tripathi, Brian Hyun-jong Lee, Alejandro Strachan

    Learn about blockchain with apps and interactive computing

13. Blockchain and Proof of Work Lab

    Online Presentations | 25 Apr 2023 | Contributor(s):: Oneal Douglin, Yu-Chung Chang, Alfonso Daniel Meraz, Brian Hyun-jong Lee, Shivam Tripathi, Alejandro Strachan

    Blockchain is a technology for a distributed, tamperproof ledger, with untrusted agents.

14. Calibration using DAKOTA

    Tools | 21 Mar 2019 | Contributor(s):: Saaketh Desai, Alejandro Strachan

    Uses DAKOTA to perform deterministic and Bayesian calibration

15. Chemical Autoencoder for Latent Space Enrichment

    Tools | 19 Sep 2019 | Contributor(s):: Bryan Arciniega, Mackinzie S Farnell, Nicolae C Iovanac, Brett Matthew Savoie

    Chemical Autencoder uses machine learning for property prediction

16. Citrine Tools for Materials Informatics

    Tools | 05 Dec 2019 | Contributor(s):: Juan Carlos Verduzco Gastelum, Alejandro Strachan

    Jupyter notebooks for sequential learning in the context of materials design. Run your own models, explore various methods and adapt the notebooks to your needs.

17. Composite Filament Simulation 3D

    Tools | 15 Feb 2019 | Contributor(s):: Zachary Yun, Michelle Zhang, Ganesh Vurimi, Hayden Taylor, Sixian Jia

    Simulate electrical properties of a nanowire composite filament.

18. Computational Helium

    Tools | 07 Jul 2017 | Contributor(s):: Alejandro Strachan

    This notebook solves the ground state for the helium atom computationally within the mean field approximation using four Gaussian functions as the basis set.

19. Computational Hydrogen

    Tools | 09 May 2017 | Contributor(s):: Martin Hunt, Alejandro Strachan

    Solve the ground state for the hydrogen atom computationally using four gaussian functions as the basis set. You can change the width of each gaussian and explore how the description changes. Compare the energy and wave function with the exact solution.

20. Computational Hydrogen Notebook

    Tools | 09 May 2017 | Contributor(s):: Martin Hunt, Alejandro Strachan

    Solve the ground state for the hydrogen atom computationally using four gaussian functions as the basis set. You can change the width of each gaussian and explore how the description changes. Compare the energy and wave function with the exact solution.