Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Distribution of Molecular Speeds01:27

Distribution of Molecular Speeds

6.0K
The motion of molecules in a gas is random in magnitude and direction for individual molecules, but a gas of many molecules has a predictable distribution of molecular speeds. This predictable distribution of molecular speeds is known as the Maxwell-Boltzmann distribution. The distribution of molecular speeds in liquids is comparable to that of gases but not identical and can help to understand the phenomenon of the boiling and vapor pressure of a liquid. Consider that a molecule requires a...
6.0K
Parallel Processing01:20

Parallel Processing

883
The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...
883
Molecular Models02:00

Molecular Models

45.5K
Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.
45.5K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Prediction of diffusion coefficients in mixtures with tensor completion.

Physical chemistry chemical physics : PCCP·2026
Same author

Quantitative Modeling of Properties in the Extended Critical Region Requires Three-Body Interactions.

Journal of chemical theory and computation·2026
Same author

Thermodynamic properties of Lennard-Jones fluids residing in two to five spatial dimensions.

The Journal of chemical physics·2026
Same author

Enabling Quantitative Benchtop <sup>13</sup>C NMR Spectroscopy in Fast Continuous Flow.

Magnetic resonance in chemistry : MRC·2026
Same author

Thermodynamically consistent machine learning model for excess Gibbs energy.

Nature communications·2026
Same author

Influence of dipole moment and anisotropy on entropy scaling of Stockmayer and diatomic fluids.

The Journal of chemical physics·2026
Same journal

Knowledge Distillation of a Protein Language Model Yields a Foundational Implicit Solvent Model.

Journal of chemical theory and computation·2026
Same journal

Generalizable Protein Folding Pathway Exploration with DA2-GRASP: Extending Beyond Miniproteins.

Journal of chemical theory and computation·2026
Same journal

Improving PCM in Protic Media: Markov State Models for TD-DFT Calculations.

Journal of chemical theory and computation·2026
Same journal

Efficient Coupled-Cluster Python Frameworks for Next-Generation GPUs: A Comparative Study of CuPy and PyTorch on the Hopper and Grace Hopper Architecture.

Journal of chemical theory and computation·2026
Same journal

Extending the MARTINI 3 Coarse-Grained Force Field to Polypeptoids.

Journal of chemical theory and computation·2026
Same journal

Statistical Mechanics of Density- and Temperature-Dependent Potentials: Application to Condensed Phases within GenDPDE.

Journal of chemical theory and computation·2026
See all related articles

Related Experiment Video

Updated: Mar 29, 2026

Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package
06:37

Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package

Published on: September 17, 2021

5.2K

ls1 mardyn: The Massively Parallel Molecular Dynamics Code for Large Systems.

Christoph Niethammer1, Stefan Becker2, Martin Bernreuther1

  • 1High Performance Computing Center Stuttgart , Nobelstr. 19, 70569 Stuttgart, Germany.

Journal of Chemical Theory and Computation
|November 21, 2015
PubMed
Summary
This summary is machine-generated.

LS1 mardyn is a highly scalable molecular dynamics simulation code. It achieves world-record simulation sizes, enabling new research in complex systems and large-scale phenomena.

More Related Videos

Author Spotlight: Streamlining Visual Dynamics to Simplify Molecular Dynamics Simulations Using Gromacs
05:00

Author Spotlight: Streamlining Visual Dynamics to Simplify Molecular Dynamics Simulations Using Gromacs

Published on: August 9, 2024

2.1K
Rapid in-silico Battery Electrolyte Electrochemical Reaction Generation using 3T-VASP Multi-Scale Energy Minimization
05:37

Rapid in-silico Battery Electrolyte Electrochemical Reaction Generation using 3T-VASP Multi-Scale Energy Minimization

Published on: August 22, 2025

772

Related Experiment Videos

Last Updated: Mar 29, 2026

Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package
06:37

Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package

Published on: September 17, 2021

5.2K
Author Spotlight: Streamlining Visual Dynamics to Simplify Molecular Dynamics Simulations Using Gromacs
05:00

Author Spotlight: Streamlining Visual Dynamics to Simplify Molecular Dynamics Simulations Using Gromacs

Published on: August 9, 2024

2.1K
Rapid in-silico Battery Electrolyte Electrochemical Reaction Generation using 3T-VASP Multi-Scale Energy Minimization
05:37

Rapid in-silico Battery Electrolyte Electrochemical Reaction Generation using 3T-VASP Multi-Scale Energy Minimization

Published on: August 22, 2025

772

Area of Science:

  • Computational Physics
  • Materials Science
  • Chemistry

Background:

  • Molecular dynamics simulations are crucial for understanding material properties at the atomic level.
  • Existing simulation codes often face limitations in scalability and the size of systems they can handle.
  • Bridging the gap between atomistic simulations and macroscopic phenomena requires efficient computational tools.

Purpose of the Study:

  • To present the LS1 mardyn code, a novel molecular dynamics simulation software.
  • To highlight its capabilities in handling large-scale simulations and complex physical models.
  • To demonstrate its potential for advancing research in various scientific domains.

Main Methods:

  • Development of a highly scalable code optimized for massively parallel supercomputing architectures.
  • Implementation of an efficient dynamic load balancing scheme for heterogeneous configurations.
  • Support for multicenter rigid potential models including Lennard-Jones sites, point charges, and higher-order polarities.

Main Results:

  • LS1 mardyn achieves world-record performance for the largest molecular simulations, exceeding four trillion particles.
  • The code demonstrates high scalability and efficiency, even for complex system setups.
  • It enables simulations on length and time scales previously inaccessible to molecular dynamics.

Conclusions:

  • LS1 mardyn is a powerful and versatile tool for large-scale molecular dynamics simulations.
  • Its modular design allows for future extensions and adaptation to new physical models and algorithms.
  • Potential applications span complex geometries, interfacial phenomena, and non-equilibrium processes like heat and mass transfer.