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Integrating Programming and Cheminformatics into the Molecular Science Curriculum: Resources from the Molecular Sciences Software Institute using nanoHUB
Online Presentations | 31 Jan 2024 | Contributor(s):: Ashley Ringer McDonald
This presentation will describe open-source curriculum from the Molecular Sciences Software Institute (the MolSSI) to teach programming and cheminformatics using nanoHUB. The MolSSI is an NSF-funded institute that aims to improve software, education, and training in the computational molecular...
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Scientific Data Visualization using Python
Online Presentations | 09 Jun 2022 | Contributor(s):: Jessica Nash, Ashley Ringer McDonald
This lecture looks at scientific data visualization using matplotlib, plotly, and visulizing molecular structures using scientific NGLView.
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Active Learning via Bayesian Optimization for Materials Discovery
Online Presentations | 25 Jun 2021 | Contributor(s):: Hieu Doan, Garvit Agarwal
In this tutorial, we will demonstrate the use of active learning via Bayesian optimization (BO) to identify ideal molecular candidates for an energy storage application.
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An Introduction to Machine Learning for Materials Science: A Basic Workflow for Predicting Materials Properties
Online Presentations | 25 Jun 2021 | Contributor(s):: Benjamin Afflerbach
This tutorial will introduce core concepts of machine learning through the lens of a basic workflow to predict material bandgaps from material compositions.
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The Materials Simulation Toolkit for Machine Learning (MAST-ML): Automating Development and Evaluation of Machine Learning Models for Materials Property Prediction
Online Presentations | 25 Jun 2021 | Contributor(s):: Ryan Jacobs
This tutorial contains an introduction to the use of the Materials Simulation Toolkit for Machine Learning (MAST-ML), a python package designed to broaden and accelerate the use of machine learning and data science methods for materials property prediction.
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Parsimonious Neural Networks Learn Interpretable Physical Laws
Online Presentations | 21 Jun 2021 | Contributor(s):: Saaketh Desai
Machine learning methods are widely used as surrogate models in the physical sciences, but less explored is the use of machine learning to discover interpretable laws from data. This tutorial introduces parsimonious neural networks (PNNs), a combination of neural networks and evolutionary...
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S4 Tutorial P1: Overview and Example 1 - Plane Wave Incident on Air-Glass Interface
Online Presentations | 08 Apr 2021 | Contributor(s):: Jie Zhu, Enas Sakr, Peter Bermel
This presentation is part of the three part tutorial for the S4 tool (Stanford Stratified Structure Solver) on nanoHUB designed for the nanoHUB IGNITE challenge. In the tutorial, we give an overview of the S4 electromagnetic simulation tool, and demonstrate the basic features through three...
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Convenient and efficient development of Machine Learning Interatomic Potentials
Online Presentations | 09 Mar 2021 | Contributor(s):: Yunxing Zuo
This tutorial introduces the concepts of machine learning interatomic potentials (ML-IAPs) in materials science, including two components of local environment atomic descriptors and machine learning models.
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Constructing Accurate Quantitative Structure-Property Relationships via Materials Graph Networks
Online Presentations | 09 Mar 2021 | Contributor(s):: Chi Chen
This tutorial covers materials graph networks for modeling crystal and molecular properties. We will introduce the graph representation of crystals and molecules and how the convolutional operations are carried out on the materials graphs.
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U-Net Convolutional Neural Networks for Image Segmentation: Application to Scanning Electron Microscopy Images of Graphene
Online Presentations | 01 Feb 2021 | Contributor(s):: Aagam Rajeev Shah
This tutorial introduces you to U-Net, a popular convolutional neural network commonly developed for image segmentation in biomedicine. Using an assembled data set, you will learn how to create and train a U-Net neural network, and apply it to segment scanning electron microscopy images of...
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Unsupervised Clustering Methods for Image Segmentation: Application to Scanning Electron Microscopy Images of Graphene
Online Presentations | 27 Jan 2021 | Contributor(s):: Aagam Rajeev Shah
This tutorial will introduce you to some basic image segmentation techniques driven by unsupervised machine learning techniques such as the Gaussian mixture model and k-means clustering. You will learn how to implement k-means clustering and template matching, and use these to segment a...
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Machine Learning Framework for Impurity Level Prediction in Semiconductors
Online Presentations | 15 Dec 2020 | Contributor(s):: Arun Kumar Mannodi Kanakkithodi
In this work, we perform screening of functional atomic impurities in Cd-chalcogenide semiconductors using high-throughput computations and machine learning.
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Running a Python 3 Script in a nanoHUB Jupyter Notebook
Online Presentations | 01 May 2020 | Contributor(s):: Tanya Faltens
This tutorial will show you how to create and run Python 3 code in a Jupyter notebook, rather than creating and running a Python script. We are working along with Chapter 1.8 “Writing a program” in the Python for Everybody course. In this lesson they execute a Python script that...
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Setting up Your nanoHUB File Structure in Jupyter Notebooks
Online Presentations | 17 Apr 2020 | Contributor(s):: Tanya Faltens
This tutorial takes you through the steps to set up your nanoHUB file structure in Jupyter Notebooks.Be sure to get a copy of the pdf that accompanies the video instructions by clicking on the Supporting Docs tab for this resource.
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Basics of Compact Model Development
Online Presentations | 02 Aug 2014 | Contributor(s):: Sivakumar P Mudanai
This tutorial is aimed at developing an understanding of what a compact model is, the need and role of compact models in the semiconductor industry and the requirements that a compact model must meet for acceptable use in circuit simulations. The tutorial will use simple examples from planar...
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NEMO5 Tutorial 5A: Devi ce Simulation - Quantum Dots
Online Presentations | 17 Jul 2012 | Contributor(s):: Jean Michel D Sellier
This presentation introduces the capabilities of NEMO5 to simulate quantum dots.
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NEMO5 Tutorial 3: Models
Online Presentations | 17 Jul 2012 | Contributor(s):: Jean Michel D Sellier
This tutorial presents the models implemented in NEMO5. A description on how the solvers interact with each other is reported along with the options of the various solvers. An example on how to make a simulation that involves strain calculations, Schroedinger wave functions calculations and an...
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The Pioneers of Quantum Computing
Online Presentations | 19 Nov 2010 | Contributor(s):: David P. Di Vincenzo
This talk profiles the persons whose insights and visions created the subject of quantum information science. Some famous, some not, they all thought deeply about the puzzles and contradictions that were apparent to the founders of quantum theory. After many years of germination, the confluence...
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Nano*High: Nature's Nasty Nanomachines: How Viruses Work, and How We Can Stop Them
Online Presentations | 25 Sep 2010 | Contributor(s):: Carolyn R. Bertozzi
The birth and growth of nanotechnology is only a few decades old, whereas Nature has been building nano-machines for millennia. Viruses are marvels of natural nano-engineering, but can pose a problem for human health. To combat these nano-machines, scientists are turning to recent developments...
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Nano*High: X-rays, Lasers, and Molecular Movies
Online Presentations | 25 Sep 2010 | Contributor(s):: Roger W. Falcone
X-ray imaging is an excellent method to make visible what would normally be invisible - who hasn't had an X-ray at the doctor or dentist's office before? At the Lawrence Berkeley National Lab, the Advanced Light Source is a gigantic X-ray imaging machine. Dr. Roger Falcone discusses X-ray...