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Resources (181-200 of 1066)

1. Ice Cream Break with Nanoscience: Nucleations and Colloid Suspensions

   Teaching Materials | 06 Jan 2020 | Contributor(s):: Raeanne L. Napoleon, Marilyn Garza, NNCI Nano

   This lesson is designed to demonstrate how liquid nitrogen cools a mixture at such a rapid rate that it precipitates extremely fine ice crystals from a homogeneous mixture of cream and other ingredients. It is also designed to show how ice cream can be made smoother and creamier through...

2. Demonstrations for the Materials Science Classroom

   Teaching Materials | 06 Jan 2020 | Contributor(s):: Silas Brown, Jud Ready, NNCI Nano

   This is a compendium of demonstrations exploring the properties of materials. Material science is the study of the five classes of material: metals, ceramics/glasses, polymers, semiconductors, and composites, and their applicable properties.  It is an exceedingly important subject because...

3. Manufacturing Fit-for-Purpose Membranes from Nanostructured Polymers

   Online Presentations | 11 Dec 2019 | Contributor(s):: William Phillip

   This presentation will discuss how to produce block polymers membranes that contain a high density of well-defined nanoscale pores using facile and scalable techniques. Furthermore, we will describe how the performance profile of the membranes can be tailored to effect selective separations...

4. 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.

5. Simulating Precipitate Morphology using a Phase Field Model

   Teaching Materials | 01 Dec 2019 | Contributor(s):: Susan P Gentry, Stephen DeWitt, Mingwei Zhang

   For this activity, students investigate how precipitate morphology is affected by materials parameters such as anisotropic interfacial energy and misfit strain. They vary the materials parameters in a series of simulations utilizing the nanoHUB tool PRISMS-PF...

6. Materials Science Modules with Molecular Dynamics

   Series | 25 Nov 2019 | Contributor(s):: Sam Reeve, Alejandro Strachan

   This module uses the Nanomaterial Mechanics Explorer: https://nanohub.org/tools/nanomatmech

7. Latest Developments in the Field of the Metal-Insulator Transition in Two Dimensions

   Online Presentations | 11 Nov 2019 | Contributor(s):: Sergey Kravchenko

   Ignited by the discovery of the metal-insulator transition, the behavior of low-disorder two-dimensional (2D) electron systems is currently the focus of a great deal of attention.  In the strongly-interacting limit, electrons are expected to crystallize into a quantum Wigner crystal...

8. Electrochromic Polymers: Transitioning Chemistry to Materials Science and Beyond

   Online Presentations | 07 Nov 2019 | Contributor(s):: John R. Reynolds

   In this lecture, we will address the synthesis and processing of π-conjugated electrochromic polymers (ECPs), as they are considered for reflective display and absorptive/transmissive (window-type) devices. In our work, we address the processing gap that was holding back developments in...

9. Bridging the Gap Between Large and Small: Thermofluids and Nanoengineering for the Water-Energy Nexus

   Online Presentations | 05 Nov 2019 | Contributor(s):: David M. Warsinger

   Nanomaterial self-assembly techniques can be guided by thermofluids designs to make macro-scale membrane systems with photonic properties for catalysis and solar distillation.

10. 3 min Research Talk: Hierarchical Material Optimization using Neural Networks

    Online Presentations | 29 Oct 2019 | Contributor(s):: Miguel Arcilla Cuaycong

    In this presentation, we sought to use a neural network (NN) to identify optimal arrangements of four different constituents in a tape spring to be used as snapping mechanisms in phase transforming cellular material that can dissipate energy.

11. ME 697R Lecture 5.2: First Principles Method - Electronic Structure of Solids

    Online Presentations | 29 Oct 2019 | Contributor(s):: Xiulin Ruan

12. Hierarchical material optimization

    Tools | 28 Oct 2019 | Contributor(s):: Miguel Arcilla Cuaycong

    Assembles all possible configurations of a structural level in a Hierarchical Material.

13. Henry Coefficient Simulator

    Tools | 23 Oct 2019 | Contributor(s):: Julian C Umeh, Thomas A Manz

    Calculate Henry's constant of several sites on a nanoporous material

14. Broadband Ferromagnetic Resonance Spectroscopy: The “Swiss Army Knife” for Understanding Spin–Orbit Phenomena

    Online Presentations | 23 Oct 2019 | Contributor(s):: Justin Shaw

    I will begin this lecture with a basic introduction to spin-orbit phenomena, followed by an overview of modern broadband FMR techniques and analysis methods. I will then discuss some recent successes in applying broadband FMR to improve our ability to control damping in metals and half-metals,...

15. Biological 3D Structures by Cryo-EM: Challenges in Computations and Instruments

    Online Presentations | 23 Oct 2019 | Contributor(s):: Wen Jiang

    Single particle cryo-EM is revolutionizing structural biology. Many structures of viruses and protein complexes have been determined to 2-4 Å resolutions. While stable structures that can be expressed/purified in large quantities can be solved routinely, the dynamic compositions and...

16. 3 min Research Talk: Web-based Machine Learning Tool for Material Discovery and Property Prediction

    Online Presentations | 26 Sep 2019 | Contributor(s):: Bryan Arciniega

    This model allows the end-user to increase their knowledge on a scarce data set by using a data-rich property set. We also investigate the effect of chemical representation and autoencoder type on property prediction and compound generation.

17. 3 min Research Talk: Using Machine Learning for Materials Discovery and Property Prediction

    Online Presentations | 26 Sep 2019 | Contributor(s):: Mackinzie S Farnell

    Machine Learning models present a transformative method of optimization and prediction in science and engineering research. In the chemical sciences, unsupervised deep learning models such as autoencoders have shown to be useful for property prediction and material...

18. 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

19. Data Science and Machine Learning for MSE Students: introduction and Hands-on Activities

    Teaching Materials | 10 Sep 2019 | Contributor(s):: Alejandro Strachan, Juan Carlos Verduzco Gastelum, Saaketh Desai

    This document introduces basic concepts of data science and machine learning in the context of materials science applications. The focus is on hands-on activities where readers use open, online tools in nanoHUB to explore the concepts being introduced. Topics covered include querying data...

20. Solid Oxide Hydrogen Fuel Cell

    Teaching Materials | 29 Aug 2019

    Solve the steady-state radial diffusion equation in a cylinder to calculate the flux through a tubular fuel cell, then set up the equations to calculate the oxygen concentration field inside the fuel cell and the total power produced.