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.

Resources (41-60 of 197)

  1. Martensitic Transformations with Molecular Dynamics

    Teaching Materials | 21 Feb 2019 | Contributor(s):: Sam Reeve, Alejandro Strachan

    In this computational lab you will perform online molecular dynamics (MD) simulations through nanoHUB of martensitic transformations and analyze the results in order to: Describe the atomistic process of martensitic, solid-solid phase transitions Compare different martensitic alloys,...

  2. Melting with Molecular Dynamics

    Teaching Materials | 21 Feb 2019 | Contributor(s):: Sam Reeve, Alejandro Strachan

    In this computational lab you will perform online molecular dynamics (MD) simulations through nanoHUB to melt nickel samples and analyze the results in order to: Understand the process of melting at atomic scales Identify effects of surfaces and specimen size Describe differences...

  3. Nanoscale Tensile Testing with Molecular Dynamics

    Teaching Materials | 21 Feb 2019 | Contributor(s):: Sam Reeve, Alejandro Strachan

    In this computational lab you will perform online molecular dynamics (MD) simulations through nanoHUB of single-crystal copper nanowires under uniaxial tension of varying orientations and analyze the results in order to: Observe how slip planes in single-crystal nanowires are formed and...

  4. Dislocation Structure and Propagation with Molecular Dynamics

    Teaching Materials | 20 Feb 2019 | Contributor(s):: Sam Reeve, Alejandro Strachan

    In this computational lab you will learn about dislocations via online molecular dynamics (MD) simulations using nanoHUB. The simulations involve various types of dislocations in FCC and BCC crystals.

  5. Ductile and Brittle Failure in Metals with Molecular Dynamics

    Teaching Materials | 20 Feb 2019 | Contributor(s):: Sam Reeve, Alejandro Strachan

    In this computational lab you will perform online molecular dynamics (MD) simulations of nanoscale cracks under uniaxial tension through nanoHUB. Simulations with varying temperature and crystal structure will provide information to: Distinguish the atomistic mechanisms of ductile and...

  6. Nanoparticle Assembly Lab

    Tools | 28 Jan 2019 | Contributor(s):: Nicholas Brunk, JCS Kadupitiya, Masaki Uchida, Douglas, Trevor, Vikram Jadhao

    Simulate assembly of nanoparticles into aggregates in physiological conditions.

  7. Calculating heat of fusion of polyethylene using Polymer Modeler

    Teaching Materials | 28 Jan 2019 | Contributor(s):: Lorena Alzate-Vargas, Benjamin P Haley, Alejandro Strachan

    The main objective of this Learning Module is to determine the heat of fusion of a polytheylene sample using molecular dynamics.

  8. Molecular Dynamics Simulation of Displacement Cascade in Molybdenum

    Presentation Materials | 06 Dec 2018 | Contributor(s):: Gyuchul Park, Alejandro Strachan

    Displacement cascade in molybdenum was conducted by using Molecular Dynamics (MD) Simulation method. LAMMPS tool was used to run the simulation at nanoHUB. Three primary questions were answered from the simulation:1. The number of displaced atoms/interstitials with respect to time when the...

  9. FunUQ for MD

    Tools | 22 Oct 2018 | Contributor(s):: Sam Reeve, Alejandro Strachan

    Functional uncertainty quantification for molecular dynamics

  10. Graphene Nanopore Drilling

    Tools | 27 Sep 2018 | Contributor(s):: Jae Hyun Park, Darren K Adams, Narayan Aluru

    Drilling a nanopore in graphene by Si-nanoparticle bombardment

  11. Combustion in Nanobubbles (generated from water electrolysis)

    Presentation Materials | 27 Aug 2018 | Contributor(s):: Shourya Jain, Li Qiao

    A long-pursued goal, which is also a grand challenge, in nanoscience and nanotechnology is to create nanoscale devices, machines and motors that can do useful work. However, loyal to the scaling law, combustion would be impossible at nanoscale be- cause the heat loss would profoundly dominate...

  12. LAMMPS Structure Analysis Toolkit

    Tools | 01 Aug 2018 | Contributor(s):: Nicholas J Finan, Saaketh Desai, Sam Reeve, Alejandro Strachan

    Perform structural analysis on trajectories in LAMMPS dump format

  13. Nanosphere Electrostatics Lab

    Tools | 22 May 2018 | Contributor(s):: JCS Kadupitiya, Nicholas Brunk, Sohile Ali, Fox, Geoffrey C., Vikram Jadhao

    The Nanosphere Electrostatics Lab empowers users to simulate the self-assembly of ions near a spherically shaped nanoparticle, and extract the effective electrostatic properties.

  14. Focused Ion Beam Molecular Dynamics

    Tools | 24 Apr 2018 | Contributor(s):: Joshua Michael Stout, Sixian Jia

    3-D Molecular Dynamics Simulation of a Gallium FIB on Silicon

  15. Ions in Nanoconfinement

    Tools | 22 Dec 2017 | Contributor(s):: Kadupitige Kadupitiya, Nasim Anousheh, Suresh Marru, Fox, Geoffrey C., Vikram Jadhao

    The Ions in Nanoconfinement app empowers users to simulate ions confined between material surfaces that are nanometers apart, and extract the associated ionic structure.

  16. LAMMPS Data-File Generator

    Tools | 01 Aug 2017 | Contributor(s):: Carlos Miguel Patiño, Lorena Alzate-Vargas, Chunyu Li, Benjamin P Haley, Alejandro Strachan

    The LAMMPS Data-File Generator generates LAMMPS data files to perform molecular dynamics simulations in LAMMPS using Dreiding or PCFF force field energy terms

  17. Atomistic Polymer Workflow Notebook

    Tools | 19 Oct 2017 | Contributor(s):: Benjamin P Haley

    Run PolymerModeler and nuSIMM tools to create atomistic polymer systems

  18. THERMAL CNT

    Tools | 23 May 2017 | Contributor(s):: Luca Bergamasco, Matteo Fasano, Eliodoro Chiavazzo, Pietro Asinari, Annalisa Cardellini, Matteo Morciano

    Compute thermal conductivity of single-walled carbon nano-tubes via NEMD method

  19. Applying Machine Learning to Computational Chemistry: Can We Predict Molecular Properties Faster without Compromising Accuracy?

    Presentation Materials | 26 Jul 2017 | Contributor(s):: Hanjing Xu, Pradeep Kumar Gurunathan

    Non-covalent interactions are crucial in analyzing protein folding and structure, function of DNA and RNA, structures of molecular crystals and aggregates, and many other processes in the fields of biology and chemistry. However, it is time and resource consuming to calculate such interactions...

  20. Structure-Force Field Generator for Molecular Dynamics Simulations

    Online Presentations | 01 Aug 2017 | Contributor(s):: Carlos Miguel Patiño, Lorena Alzate-Vargas, Alejandro Strachan

    Atomistic and molecular simulations have become an important research field due to the progress made in computer performance and the necessity of new and improved materials. Despite this, first principle simulations of large molecules are still not possible because the high computational time and...