Tags: molecular dynamics (MD)

Description

Molecular dynamics is a form of computer simulation in which atoms and molecules are allowed to interact for a period of time by approximations of known physics, giving a view of the motion of the particles. This kind of simulation is frequently used in the study of proteins and biomolecules, as well as in materials science. More information on Molecular dynamics can be found here.

All Categories (1-20 of 250)

  1. 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

  2. Bishwajite Karmakar

    https://nanohub.org/members/336196

  3. adnan zahid

    I was born and raised in the heart of Islamabad and grew up a very outgoing and active child. Always staying proactive, I ventured into a lot of different activities to show my talent. I have...

    https://nanohub.org/members/335069

  4. The DFT calculation for Amorphous Silica is not able to process showing an error I am not able to understand.

    Closed | Responses: 1

    Whenever I am trying to perform DFT calculation of any molecule there comes the type of error which is not understandable. The recent one being for amorphous Silica stating " from pp_check_file :...

    https://nanohub.org/answers/question/2483

  5. MIT Atomic-Scale Modeling Toolkit

    15 Jan 2008 | | Contributor(s):: daniel richards, Elif Ertekin, Jeffrey C Grossman, David Strubbe, Justin Riley, Enrique Guerrero

    Tools for Atomic-Scale Modeling

  6. 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.

  7. Jonathan Patricio

    https://nanohub.org/members/304315

  8. Aminul Islam Olin

    https://nanohub.org/members/303815

  9. Issue in building large polymer system

    Closed | Responses: 1

    Is it normal to see: "submitting polymer model to remote site ..." for more than 3 hrs for a large number of chains and monomers (100 chains and 1000 monomer). The simulation is still...

    https://nanohub.org/answers/question/2392

  10. 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.

  11. 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. ...

  12. 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.

  13. 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

  14. 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...

  15. 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...

  16. 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...

  17. 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

  18. Rohit Goswami

    https://nanohub.org/members/282063

  19. Sourav Sahoo

    https://nanohub.org/members/281706

  20. 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