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Building a nanoHUB Graphical Interface for Exploring Protein Dynamics and Spectroscopy: the PigmentHunter App
18 Apr 2024 | | Contributor(s):: Safa Ahad
Running and analyzing protein molecular dynamics (MD) simulations can be time consuming and tedious. In this webinar, we introduce PigmentHunter , an online nanoHUB tool that enables “point-and-click” MD-based simulation of excitonic spectra of chlorophyll proteins based on PDB...
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Thermal Transport in Layered Materials, Devices, and Systems
11 Apr 2024 | | Contributor(s):: Eric Pop
The thermal properties of layered materials (like graphene and MoS2) are an active area of investigation, particularly due to their anisotropic and tunable thermal conductivity. We have studied their behavior as part of transistors, where self-heating is a major challenge for performance and...
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Deciphering Energy Transfer in Photosynthesis with Multiscale Molecular Modeling
07 Dec 2023 | | Contributor(s):: Lyudmila V. Slipchenko
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Exploring the Nano World: Building Nanoscale Structures with Polymer Modeler
14 Jul 2023 | | Contributor(s):: Tongtong Shen
In this 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.
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Teaching and Learning with the MIT Atomic Scale Modeling Toolkit's Classical and Quantum Atomic Modeling Applications
23 Dec 2022 | | Contributor(s):: Enrique Guerrero
We will perform molecular dynamics computations using LAMMPS, simple Monte Carlo simulations including the Ising model, and run quantum chemistry and density functional theory computations.
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LAMMPS Data File Generator Tool Demo
15 Apr 2022 | | Contributor(s):: Carlos Miguel Patiño
A quick demonstration of the nanoHUB tool LAMMPS Data-File Generator. This was developed as part of the 2017 NCN URE program.
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Visualization Dashboard for MPCAs
09 Mar 2022 | | Contributor(s):: Juan Carlos Verduzco Gastelum, Zachary D McClure, Alejandro Strachan
Sim2L Visualization Dashboard for Multi-Principal Component Allloys
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Designing Machine Learning Surrogates for Molecular Dynamics Simulations
25 Nov 2021 | | Contributor(s):: JCS Kadupitiya
Molecular dynamics (MD) simulations accelerated by high-performance computing (HPC) methods are powerful tools for investigating and extracting the microscopic mechanisms characterizing the properties of soft materials such as self-assembled nanoparticles, virus capsids, confined electrolytes,...
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Active Learning Workflow for MPCAs
05 Oct 2021 | | Contributor(s):: Juan Carlos Verduzco Gastelum, David Enrique Farache, Zachary D McClure, Saaketh Desai, Alejandro Strachan
Active learning workflow for MPCAs using MD simulation tool MeltHEAS for optimized melting temperatures
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MIT Atomic-Scale Modeling Toolkit
15 Jan 2008 | | Contributor(s):: David A Strubbe, Enrique Guerrero, daniel richards, Elif Ertekin, Jeffrey C Grossman, Justin Riley
Tools for Atomic-Scale Modeling
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Thermal Conductivity Simulator
03 Oct 2020 | | Contributor(s):: Md Shajedul Hoque Thakur, Md Mahbubul Islam
Simulate thermal conductivity of Silicon using reverse non-equilibrium molecular dynamics simulations.
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MATE 370 Virtual Lab: Exploring Phase Transformations Through nanoHUB Nanomaterial Mechanics Explorer Tool
24 Sep 2020 | | Contributor(s):: Mohsen B Kivy, Crystal Ipong
This lab explores the kinetics of phase transformation using nanoHUB tools.
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Machine Learning in Materials - Center for Advanced Energy Studies and Idaho National Laboratory
24 Sep 2020 | | Contributor(s):: Alejandro Strachan
his hands-on tutorial will introduce participants to modern tools to manage, organize, and visualize data as well as machine learning techniques to extract information from it. ...
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Molecular Dynamics Simulations for Propulsion Applications
21 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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Refractory Complex Concentrated Alloy Melting Point Calculation
25 May 2020 | | Contributor(s):: Zachary D McClure, Saaketh Desai, Alejandro Strachan
Calculate melting point of BCC-type high entropy alloys through phase coexistence method
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Parsimonious Neural Networks Learn Classical Mechanics and Can Teach It
15 May 2020 | | Contributor(s):: Saaketh Desai, Alejandro Strachan
We combine neural networks with genetic algorithms to find parsimonious models that describe the time evolution of a point particle subjected to an external potential. The genetic algorithm is designed to find the simplest, most interpretable network compatible with the training data. The...
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Hands-on Unsupervised Learning using Dimensionality Reduction via Matrix Decomposition (2nd offering)
30 Apr 2020 | | Contributor(s):: Michael N Sakano, Alejandro Strachan
This tutorial introduces unsupervised machine learning algorithms through dimensionality reduction via matrix decomposition techniques in the context of chemical decomposition of reactive materials in a Jupyter notebook on nanoHUB.org. The tool used in this demonstration...
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Hands-on Unsupervised Learning using Dimensionality Reduction via Matrix Decomposition (1st offering)
29 Apr 2020 | | Contributor(s):: Michael N Sakano, Alejandro Strachan
This tutorial introduces unsupervised machine learning algorithms through dimensionality reduction via matrix decomposition techniques in the context of chemical decomposition of reactive materials in a Jupyter notebook on nanoHUB.org. The tool used in this demonstration...
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Unsupervised learning using dimensionality reduction via matrix decomposition
14 Apr 2020 | | Contributor(s):: Michael N Sakano, Alejandro Strachan
Learn PCA and NMF via chemistry example
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High Entropy Alloy Melting Point Calculation
05 Mar 2020 | | Contributor(s):: Zachary D McClure, Saaketh Desai, Alejandro Strachan
Calculate melting point of high entropy alloys through phase coexistence method