Chemistry
Webinar Abstracts
Live Chemistry Webinar Abstracts
This page contains abstracts for our Live Chemistry Webinars
Exploring the Nano World: Building Nanoscale Structures with Polymer Modeler
June 9, 2023, 2:00 - 3:00 PM EDT
The use of polymer materials has become increasingly popular in both academic and industrial fields, with applications ranging from common plastics to advanced biomaterials. With the advancement of computational science, simulations have become an essential tool for investigating the thermodynamics of molecular-level polymer systems. Along with great progress in properties prediction with improved accuracy, great challenges still exist in modeling processing of polymer systems, especially in accurate description of dynamic evolution incorporated with various processing conditions resulting macroscopic structural changes like carbon fiber processing from polyacrylonitrile (PAN) precursor in which crystalline regions represent more than 55% of the material by volume.
During my talk, I will showcase how atomic-level simulations can lead to a more fundamental understanding of PAN crystal structures and guide you through an interactive Polymer Modeler powered by nanoHUB.
Interactive modeling of materials with density functional theory using the Quantum ESPRESSO interface within the MIT Atomic Scale Modeling Toolkit
October 26, 2022, 12:00 - 1:00 PM EDT
We will explore the Quantum ESPRESSO interface within the MIT Atomic Scale Modeling Toolkit with interactive examples. We will review the basics of density functional theory and then focus on the tool’s capabilities. This module has been used to aid in teaching condensed matter physics and could be reasonably used as a pedagogical tool in a range of courses including density functional theory, materials physics, computational physics, or similar courses. The interface is built to be simple, allowing easy-to-follow instructions to be written for students to compute. We will study examples of computing the kinetic energy cutoff, structural relaxation, Young’s modulus, electronic band structure, and Raman spectroscopy of MoS2, Si, and C systems. The tool can be used to compute some physical properties of materials by atomic-scale modeling and data is displayed live or could be plotted externally.
October 12, 2022, 12:00 - 1:00 PM EDT
In this webinar, Dr. Strubbe will discuss how he has been using the MIT Atomic-Scale Modeling Toolkit as a part of his undergraduate and graduate class on condensed matter physics. In discussion sections, simulations are performed to illustrate concepts like covalent bonding, bandstructure, phonons, and magnetic phase transitions. The course culminated in a Course-based Undergraduate Research Experience, a final project in which the students calculated structural, electronic and vibrational properties of a 2D material alloy. Dr. Strubbe will show how he used the simulation tools to help students understand condensed matter physics and ultimately make their own contribution to research. Dr. Enrique Guerrero will give a seminar on Oct 26 focusing in more detail on the Quantum ESPRESSO module within this toolkit, which was developed with new functionality to enable this project.
October 5, 2022, 1:30 - 2:30 PM EDT
Density Functional Theory is a very successful and very widespread first-principles electronic structure framework that describes the ground-state of electrons in oftentimes very good agreement with experiment. It also functions as starting point for more accurate methods such as many-body perturbation theory. In this webinar, I will briefly outline the fundamentals of this technique, and demonstrate applications to compute total energies, bulk modulus, and electronic structure/densities of states using nanoHUB.
Introduction to Machine Learning for materials science
September 13, 2022; 1:00 - 3:00 PM EDT
Part I
Part one of the workshop will introduce core concepts of machine learning through the lens of a basic workflow to predict material band gaps from their compositions. As we progress through this workflow we will highlight key steps, challenges that can come up with materials data, and potential solutions to these challenges. The core workflow includes: Data Cleaning, Feature Generation, Feature Engineering, Establishing Model Assessment, Training a Default Model, Hyperparameter Optimization, and Making Predictions. By the end of the workshop I hope that you’ll have a better understanding of these core concepts, and how they can all fit together.
Part II
Part two of the workshop is a tutorial that introduces 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. Through hands-on activities, we will use MAST-ML to (1) import materials datasets from online databases and clean and examine our input data, (2) conduct feature engineering analysis, including generation, preprocessing, and selection of features, (3) construct, evaluate and compare the performance of different model types and data splitting techniques, and (4) conduct a preliminary assessment of model error analysis and uncertainty quantification (UQ).
Data Cleaning with MATLAB
September 12, 2022; 1:00 - 2:00 PM EDT
Did you know you could easily reformat and/or analyze all your worksheet data in MATLAB? This workshop is for people who already know how to use MATLAB. If you are looking for more introductory material, check out MATLAB Training for Undergraduate Research Students on nanoHUB and this MATLAB tutorial on YouTube. This workshop will go over MATLAB built-in functions (readcell and writecell) to import data from Excel and export data to Excel. Depending on attendees and their interests, we will discuss how to import, reformat, analyze, plot, and export data.
Introduction to computational chemistry using the NUITNS simulation toolkit in nanoHUB
September 9, 2022, 1:00 - 2:00 PM EDT
In this live webinar, Dr. Tomekia Simeon will describe how she has successfully used computational chemistry assignments in her undergraduate chemistry courses at Dillard University using nanoHUB’s free online simulation resources. After a demonstration where you can follow along using the NUITNS (Northwestern University Initiative for Teaching Nanoscience) toolkit in nanoHUB (https://nanohub.org/tools/nuitns) there will be time to ask questions about teaching with this toolkit and with nanoHUB in general.
This webinar is intended for anyone interested in teaching chemistry using nanoHUB tools, whether you have a computational chemistry background or not. Please share this information with your colleagues!
Teaching electronic structure methods in chemistry using simulation tools in nanoHUB
September 7, 2022, 1:00 - 2:00 PM EDT
This webinar will give an overview of Dr. Adelstein's computational chemistry course in nanoHUB, and provide information on how she teaches these topics to her master’s and upper-division chemistry students.
Participants will get hands-on practice with lessons on Hartree-Fock and basis sets using the nanoHUB tool ORCA and the opportunity to ask questions about teaching with nanoHUB.
Hands-on Teaching with Jupyter Notebooks on nanoHUB
September 6, 2022; 1:00 - 2:00 PM EDT
Dr. Reppert will discuss his use of nanoHUB Jupyter Notebook-based content in college Chemistry courses, focusing on nanoHUB's unique possibilities for hands-on simulation, visualization, and programming projects. As examples, he will describe three specific applications of nanoHUB content to courses at Purdue:
- A stand-alone Lattice Protein simulation and visualization app used to illustrate statistical mechanics and protein-folding concepts in CHM 372 (Physical Chemistry for life science students): https://nanohub.org/tools/latticeprotein
- A nanoHUB-hosted home page for a Physical Chemistry laboratory (CHM 37301), which students use both to access lab instructions, to learn basic Python programming, and to process and visualize their experimental data: https://nanohub.org/tools/chm37301
- A nanoHUB-hosted home page for a graduate Molecular Spectroscopy course, that guides students through advanced molecular and electrodynamics simulations as a means to visualize spectroscopic processes and learn the Python programming skills necessary to run molecular simulations and process spectroscopic data: https://nanohub.org/tools/molspec/