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

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

381
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
381
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

39
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...
39
Woodward–Hoffmann Selection Rules and Microscopic Reversibility01:34

Woodward–Hoffmann Selection Rules and Microscopic Reversibility

3.0K
Electrocyclic reactions, cycloadditions, and sigmatropic rearrangements are concerted pericyclic reactions that proceed via a cyclic transition state. These reactions are stereospecific and regioselective. The stereochemistry of the products depends on the symmetry characteristics of the interacting orbitals and the reaction conditions. Accordingly, pericyclic reactions are classified as either symmetry-allowed or symmetry-forbidden. Woodward and Hoffmann presented the selection criteria for...
3.0K
Maxwell-Boltzmann Distribution: Problem Solving01:20

Maxwell-Boltzmann Distribution: Problem Solving

1.4K
Individual molecules in a gas move in random directions, but a gas containing numerous molecules has a predictable distribution of molecular speeds, which is known as the Maxwell-Boltzmann distribution, f(v).
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by
1.4K
¹H NMR: Interpreting Distorted and Overlapping Signals01:02

¹H NMR: Interpreting Distorted and Overlapping Signals

1.0K
Spin systems where the difference in chemical shifts of the coupled nuclei is greater than ten times J are called first-order spin systems. These nuclei are weakly coupled, and their chemical shifts and coupling constant can generally be estimated from the well-separated signals in the spectrum.
As Δν decreases and the signals move closer, the doublets appear increasingly distorted. The intensities of the inner lines increase at the cost of those of the outer lines as the signals are...
1.0K
IR Spectroscopy: Hooke's Law Approximation of Molecular Vibration01:16

IR Spectroscopy: Hooke's Law Approximation of Molecular Vibration

1.2K
A covalently bonded heteronuclear diatomic molecule can be modeled as two vibrating masses connected by a spring. The vibrational frequency of the bond can be expressed using an equation derived from Hooke's law, which describes how the force applied to stretch or compress a spring is proportional to the displacement of the spring. In this case, the atoms behave like masses, and the bond acts like a spring.
According to Hooke's law, the vibrational frequency is directly proportional to...
1.2K

You might also read

Related Articles

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

Sort by
Same author

Charge-Symmetry-Mediated Liquid-Liquid Phase Separation Enables Tailored High-Protein Food Models.

Biomacromolecules·2026
Same author

Remotely Tuned Triplet Transfer via Ligand Proximity in Quantum Dot-Organic Spectral Converters.

ACS nano·2026
Same author

Polymer-constrained excimer enables flexible and self-healable optoelectronic elastomer for mechanical sensor.

Nature communications·2025
Same author

Self-assembly of inverted phases in AB/CD diblock copolymer blends.

The Journal of chemical physics·2025
Same author

Erratum: "Inference of Onsager coefficient from microscopic simulations by machine learning" [J. Chem. Phys. 162, 034901 (2025)].

The Journal of chemical physics·2025
Same author

Formation and Dynamics of Imidazole Supramolecular Chains Investigated by Deep Potential Molecular Dynamics Simulation.

Langmuir : the ACS journal of surfaces and colloids·2024
Same journal

Anharmonic phonons via quantum thermal bath simulations.

The Journal of chemical physics·2026
Same journal

Quantum simulation of alignment dependent differential cross sections in co-propagating molecular beams at cold collision energies.

The Journal of chemical physics·2026
Same journal

Non-additive ion effects on the coil-globule equilibrium of a generic polymer in aqueous salt solutions.

The Journal of chemical physics·2026
Same journal

Insights into the unexpected small reduction of the temperature of maximum density of water by lithium chloride addition.

The Journal of chemical physics·2026
Same journal

Optical frequency comb double-resonance spectroscopy of the 9030-9175 cm-1 states of ethylene.

The Journal of chemical physics·2026
Same journal

Time reversal breaking of colloidal particles in cells.

The Journal of chemical physics·2026
See all related articles

Related Experiment Video

Updated: Jun 2, 2025

Experimental and Data Analysis Workflow for Soft Matter Nanoindentation
13:04

Experimental and Data Analysis Workflow for Soft Matter Nanoindentation

Published on: January 18, 2022

3.8K

Inference of Onsager coefficient from microscopic simulations by machine learning.

Kaihua Zhang1, Shuanhu Qi2, Yongzhi Ren3,4,5

  • 1School of Chemistry, Beihang University, Beijing 100191, China.

The Journal of Chemical Physics
|January 15, 2025
PubMed
Summary
This summary is machine-generated.

We developed a machine learning method to extract the Onsager coefficient for Dynamic Density Functional Theory (DDFT) from molecular simulations. This approach improves polymer dynamics modeling accuracy by directly calculating this key parameter.

More Related Videos

Analyzing Mitochondrial Morphology Through Simulation Supervised Learning
12:06

Analyzing Mitochondrial Morphology Through Simulation Supervised Learning

Published on: March 3, 2023

3.9K
Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.1K

Related Experiment Videos

Last Updated: Jun 2, 2025

Experimental and Data Analysis Workflow for Soft Matter Nanoindentation
13:04

Experimental and Data Analysis Workflow for Soft Matter Nanoindentation

Published on: January 18, 2022

3.8K
Analyzing Mitochondrial Morphology Through Simulation Supervised Learning
12:06

Analyzing Mitochondrial Morphology Through Simulation Supervised Learning

Published on: March 3, 2023

3.9K
Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.1K

Area of Science:

  • Polymer Science
  • Computational Materials Science
  • Statistical Mechanics

Background:

  • Dynamic Density Functional Theory (DDFT) is a powerful multiscale modeling approach for polymer dynamics.
  • The accuracy of DDFT is limited by the empirical derivation of its sole free parameter, the Onsager coefficient.
  • Bridging particle-based simulations and coarse-grained models remains a challenge.

Purpose of the Study:

  • To develop a novel machine learning workflow for the direct extraction of the Onsager coefficient from molecular simulations.
  • To improve the accuracy and applicability of DDFT in modeling polymer dynamics.
  • To establish a connection between dynamic correlations and system parameters in polymer melts.

Main Methods:

  • A DDFT-informed ordinary differential equation network was developed.
  • The network was trained using data from Brownian dynamics (BD) simulations of polymer density evolution.
  • The Onsager coefficient was extracted by fitting the network to BD simulation results.

Main Results:

  • The machine learning workflow successfully extracted the Onsager coefficient.
  • DDFT models utilizing the extracted Onsager coefficient accurately reproduced BD simulation results for lamellar transitions in diblock copolymers.
  • A strong correlation was identified between the Onsager coefficient, dynamic correlations (strength and length), and system parameters like the Flory-Huggins interaction parameter.

Conclusions:

  • The proposed machine learning approach provides a reliable, bottom-up method for determining the Onsager coefficient in DDFT.
  • This work establishes a direct link between dynamic correlations and thermodynamic parameters in polymer systems.
  • The developed framework offers a pathway to bridge detailed molecular simulations with coarse-grained field theories for non-equilibrium systems.