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Module 7: Active Learning for Design of Experiments
Online Presentations | 30 Sep 2020 | Contributor(s):: Alejandro Strachan, Juan Carlos Verduzco Gastelum
This module introduces active learning in the context of materials discovery with hands-on online simulations. Active learning is a subset of machine learning where the information available at a given time is used to decide what areas of space to explore next. In this module, we will explore...
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Molecular Dynamics Simulations for Propulsion Applications
Online Presentations | 26 Aug 2020 | Contributor(s):: Li Qiao
In this talk, Prof. Qiao will discuss the use of molecular dynamics simulations to examine thermodynamics, transport properties, and fluid models of supercritical fuel systems.
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Hands-on Sequential Learning and Design of Experiments
Online Presentations | 29 Apr 2020 | Contributor(s):: Juan Carlos Verduzco Gastelum, Alejandro Strachan
This tutorial introduces the concept of sequential learning and information acquisition functions and how these algorithms can help reduce the number of experiments required to find an optimal candidate. A hands-on approach is presented to optimize the ionic conductivity of ceramic...
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Synthesis of Graphene by Chemical Vapor Deposition Part II: Data Science + Graphene Synthesis
Online Presentations | 29 Apr 2020 | Contributor(s):: Sameh H Tawfick
Overall, these two lectures are meant to be a general introduction on the opportunities and challenges related to graphene synthesis.
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Synthesis of Graphene by Chemical Vapor Deposition Part I
Online Presentations | 29 Apr 2020 | Contributor(s):: Sameh H Tawfick
Overall, these two lectures are meant to be a general introduction on the opportunities and challenges related to graphene synthesis.
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Image Segmentation for Graphene Images
Online Presentations | 29 Apr 2020 | Contributor(s):: Joshua A Schiller
This lecture outlines the need for a fast, automated means for identifying regions of images corresponding to graphene. Simple methods, like color masking and template matching, are discussed initially. Unsupervised clustering methods are then introduced as potential improvements...
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ME 697R Lecture 5.5A: First Principles Method - Development of Empirical Interatomic Potentials using DFT I
Online Presentations | 18 Feb 2020 | Contributor(s):: Xiulin Ruan
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3 min. Research Talk: Identifying the Dimensionality of Crystal Structures
Online Presentations | 12 Feb 2020 | Contributor(s):: Franco Vera
Today, researchers worldwide have identified over 100,000 distinct bulk materials. The underlying dimensionality of these materials is not always clear however, and as such researchers have sought to identify stable, lower dimensional materials derived from the bulk parent structures. A team of...
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MSEML: Machine Learning for Materials Science Tool on nanoHUB
Online Presentations | 27 Jan 2020 | Contributor(s):: Saaketh Desai
This talk is a hands-on demonstration using the nanoHUB tool Machine Learning for Materials Science: Part 1.
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Data Science and Machine Learning for Materials Science
Online Presentations | 22 Jan 2020 | Contributor(s):: Saaketh Desai
This talk covers the fundamentals of machine learning and data science, focusing on material science applications. The talk is for a general audience, attempting to introduce basic concepts such as linear regression, supervised learning with neural networks including forward and back...
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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...
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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...
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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...
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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.
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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.
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ME 697R Lecture 5.2: First Principles Method - Electronic Structure of Solids
Online Presentations | 29 Oct 2019 | Contributor(s):: Xiulin Ruan
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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,...
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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...
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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.
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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...