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

Mean free path and Mean free time01:22

Mean free path and Mean free time

4.9K
Consider the gas molecules in a cylinder. They move in a random motion as they collide with each other and change speed and direction. The average of all the path lengths between collisions is known as the "mean free path."
4.9K
Distribution of Molecular Speeds01:27

Distribution of Molecular Speeds

5.2K
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...
5.2K
Step-Growth Polymerization: Overview01:03

Step-Growth Polymerization: Overview

4.2K
Step-growth or condensation polymerization is a stepwise reaction of bi or multifunctional monomers to form long-chain polymers. As all the monomers are reactive, most of the monomers are consumed at the early stages of the reaction to form small chains of reactive oligomers, which then combine to form long polymer chains in the late stages. Hence, the reaction has to proceed for a long time to achieve high molecular weight polymers.
Many natural and synthetic polymers are produced by...
4.2K
Principle of Linear Impulse and Momentum for a System of Particles01:21

Principle of Linear Impulse and Momentum for a System of Particles

550
In the context of a system of particles moving relative to an inertial frame of reference, the equation of motion is a crucial tool for understanding the dynamics of the system. This equation, which accounts for external forces acting on each particle, plays a fundamental role in describing the system's behavior.
Notably, internal forces between particles, occurring in equal and opposite collinear pairs, cancel out and are not part of the equation of motion. This exclusion simplifies the...
550
Principle of Linear Impulse and Momentum for a Single Particle: Problem Solving01:23

Principle of Linear Impulse and Momentum for a Single Particle: Problem Solving

954
Consider a wooden box and a cylinder of known masses m1 and m2, respectively,  hanging from a ceiling with the help of a massless pulley system.
954
Velocity and Position by Integral Method01:13

Velocity and Position by Integral Method

7.3K
If acceleration as a function of time is known, then velocity and position functions can be derived using integral calculus. For constant acceleration, the integral equations refer to the first and second kinematic equations for velocity and position functions, respectively.
Consider an example to calculate the velocity and position from the acceleration function. A motorboat is traveling at a constant velocity of 5.0 m/s when it starts to decelerate to arrive at the dock. Its acceleration is...
7.3K

You might also read

Related Articles

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

Sort by
Same author

Nonadiabatic Force Matching for Alchemical Free-Energy Estimation.

Journal of chemical theory and computation·2025
Same author

Variational time reversal for free-energy estimation in nonequilibrium steady states.

Physical review. E·2024
Same author

OrbNet Denali: A machine learning potential for biological and organic chemistry with semi-empirical cost and DFT accuracy.

The Journal of chemical physics·2021
Same author

Multiscale modeling of genome organization with maximum entropy optimization.

The Journal of chemical physics·2021
Same author

Analytical gradients for molecular-orbital-based machine learning.

The Journal of chemical physics·2021
Same author

Improved accuracy and transferability of molecular-orbital-based machine learning: Organics, transition-metal complexes, non-covalent interactions, and transition states.

The Journal of chemical physics·2021
Same journal

The influence of chirality on the macroscopic behavior of multiferroic smectic phases.

The Journal of chemical physics·2026
Same journal

Polaron transformed canonically consistent quantum master equation.

The Journal of chemical physics·2026
Same journal

The x-ray absorption spectrum of the propargyl radical C3H3●.

The Journal of chemical physics·2026
Same journal

Transient hydroperoxyalkyl intermediates (•QOOH) in isopentane oxidation. I. Conformer- and isomer-resolved infrared spectra.

The Journal of chemical physics·2026
Same journal

Transient hydroperoxyalkyl intermediates (•QOOH) in isopentane oxidation. II. Isomer-resolved unimolecular dynamics.

The Journal of chemical physics·2026
Same journal

Quantum state-to-state dynamics studies of the C(3P) + OH(X2Π) → CO(a3Π) + H(2S) reaction based on a new HCO(12A″) potential energy surface.

The Journal of chemical physics·2026
See all related articles

Related Experiment Video

Updated: Jan 4, 2026

Exploring Caspase Mutations and Post-Translational Modification by Molecular Modeling Approaches
05:56

Exploring Caspase Mutations and Post-Translational Modification by Molecular Modeling Approaches

Published on: October 13, 2022

1.7K

Path-accelerated stochastic molecular dynamics: Parallel-in-time integration using path integrals.

Jorge L Rosa-Raíces1, Bin Zhang2, Thomas F Miller1

  • 1Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California 91125, USA.

The Journal of Chemical Physics
|November 3, 2019
PubMed
Summary
This summary is machine-generated.

We introduce path-accelerated molecular dynamics (MD) to speed up simulations using distributed computing. This method parallelizes time steps, significantly reducing computation time for MD trajectories.

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

1.8K
A Protocol for Real-time 3D Single Particle Tracking
10:16

A Protocol for Real-time 3D Single Particle Tracking

Published on: January 3, 2018

15.3K

Related Experiment Videos

Last Updated: Jan 4, 2026

Exploring Caspase Mutations and Post-Translational Modification by Molecular Modeling Approaches
05:56

Exploring Caspase Mutations and Post-Translational Modification by Molecular Modeling Approaches

Published on: October 13, 2022

1.7K
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

1.8K
A Protocol for Real-time 3D Single Particle Tracking
10:16

A Protocol for Real-time 3D Single Particle Tracking

Published on: January 3, 2018

15.3K

Area of Science:

  • Computational Physics
  • Chemical Physics
  • Materials Science

Background:

  • Long-time scale molecular dynamics (MD) simulations are computationally intensive.
  • Massively parallel architectures offer potential for accelerating these simulations.

Purpose of the Study:

  • To introduce a novel method for accelerating MD simulations using distributed computing.
  • To reduce the wall-clock time required for integrating MD trajectories.

Main Methods:

  • Developed the path-accelerated molecular dynamics method, parallelizing MD time steps.
  • Expressed system time evolution using path integrals for numerical integration.
  • Initialized path configurations from a nonequilibrium distribution.

Main Results:

  • Achieved significant speedups in integrating MD trajectories.
  • Reduced wall-clock time by over three orders of magnitude for a harmonic oscillator.
  • Reduced wall-clock time by over two orders of magnitude for a Lennard-Jones liquid.

Conclusions:

  • Path-accelerated MD offers substantial performance gains for long-time scale simulations.
  • The method is generalizable to various stochastic equations of motion.
  • Combines effectively with existing parallelization techniques for further speedup.