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

Calculations of Electric Potential I01:15

Calculations of Electric Potential I

2.1K
Consider a ring of radius R with a uniform charge density λ. What will the electric potential be at point M, which is located on the axis of the ring at a distance x from the center of the ring?
The ring is divided into infinitesimal small arcs such that point M is equidistant from all the arcs. Here, the cylindrical coordinate system is used to calculate the electric potential at point M. A general element of the arc between angles θ and θ + dθ is of the...
2.1K
Calculations of Electric Potential II01:27

Calculations of Electric Potential II

1.8K
An electric dipole is a system of two equal but opposite charges, separated by a fixed distance. This system is used to model many real-world systems, including atomic and molecular interactions. One of these systems is the water molecule, but only under certain circumstances. These circumstances are met inside a microwave oven, where electric fields with alternating directions make the water molecules change orientation. This vibration is equivalent to heat at the molecular level.
Consider a...
1.8K
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

101
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
101

You might also read

Related Articles

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

Sort by
Same author

Scalable Quantum-Classical Hybrid Algorithm for Excited States Based on Divide-and-Conquer Unitary Coupled-Cluster Linear-Response Theory Using Dynamical Polarizability.

The journal of physical chemistry. A·2026
Same author

Geometry Optimization for Nonlocal Excited State Using the Divide-and-Conquer Method.

Journal of chemical theory and computation·2026
Same author

Development of a Fluctuation-Assisted Molecular Dynamics Method for the Efficient Exploration of Chemical Reactions.

The journal of physical chemistry letters·2026
Same author

Insights into proton transfer dynamics in histidine tautomers of amyloid-β (1-40).

Communications chemistry·2025
Same author

Efficient optimization of low-rank antisymmetric product of geminals wavefunction using the direct Givens rotation method.

The Journal of chemical physics·2025
Same author

Investigation of Li-Ion Hopping in Ionic-Liquid-Incorporated Methyl Cellulose/Carboxymethyl Cellulose Solid Polymer Electrolyte: A Molecular Simulation Insight.

The journal of physical chemistry. B·2025

Related Experiment Video

Updated: Sep 14, 2025

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches
10:50

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

Published on: June 21, 2022

1.8K

Large-Scale Calculations by Integrating the Fragmentation Approach With Neural Network Potentials.

Rei Oshima1, Mikito Fujinami2, Yuya Nakajima3

  • 1Department of Chemistry and Biochemistry, School of Advanced Science and Engineering, Waseda University, Tokyo, Japan.

Journal of Computational Chemistry
|July 24, 2025
PubMed
Summary

A new fragmentation method allows large-scale molecular simulations with neural network potentials (NNPs). This technique accurately reconstructs system energy, enabling simulations of over one million atoms.

Keywords:
fragmentation methodlarge‐scale calculationneural network potential

More Related Videos

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
11:18

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Published on: March 2, 2015

10.4K
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

81

Related Experiment Videos

Last Updated: Sep 14, 2025

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches
10:50

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

Published on: June 21, 2022

1.8K
Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
11:18

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Published on: March 2, 2015

10.4K
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

81

Area of Science:

  • Computational chemistry
  • Materials science
  • Molecular dynamics

Background:

  • Neural network potentials (NNPs) offer efficient molecular simulations.
  • Scaling limitations of conventional NNPs hinder large-scale system modeling.

Purpose of the Study:

  • To introduce a fragmentation method for large-scale molecular simulations using NNPs.
  • To overcome the atomistic limitations of current NNP simulations.

Main Methods:

  • System partitioning into cube-shaped fragments.
  • Many-body expansion formalism for energy reconstruction.
  • Distance-based cut-off approximation.

Main Results:

  • Accurate energy reconstruction with three-body interactions and 26 neighbors.
  • Per-atom energy error reduced to within 0.04 eV for various crystals.
  • Enabled simulations of systems up to 1 million atoms.
  • Scaling exponent below 1.64 for three-body calculations.

Conclusions:

  • The fragmentation method significantly enhances the scale of NNP simulations.
  • The approach is computationally feasible for extremely large systems.
  • Opens possibilities for simulating complex materials and phenomena at unprecedented scales.