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

Van der Waals Equation01:10

Van der Waals Equation

4.2K
The ideal gas law is an approximation that works well at high temperatures and low pressures. The van der Waals equation of state (named after the Dutch physicist Johannes van der Waals, 1837−1923) improves it by considering two factors.
First, the attractive forces between molecules, which are stronger at higher densities and reduce the pressure, are considered by adding to the pressure a term equal to the square of the molar density multiplied by a positive coefficient a. Second, the volume...
4.2K
Molecular Models02:00

Molecular Models

38.6K
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.
38.6K
Maxwell-Boltzmann Distribution: Problem Solving01:20

Maxwell-Boltzmann Distribution: Problem Solving

1.6K
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
1.6K
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

569
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...
569
Real Gases: Effects of Intermolecular Forces and Molecular Volume Deriving Van der Waals Equation04:01

Real Gases: Effects of Intermolecular Forces and Molecular Volume Deriving Van der Waals Equation

34.7K
Thus far, the ideal gas law, PV = nRT, has been applied to a variety of different types of problems, ranging from reaction stoichiometry and empirical and molecular formula problems to determining the density and molar mass of a gas. However, the behavior of a gas is often non-ideal, meaning that the observed relationships between its pressure, volume, and temperature are not accurately described by the gas laws. 
34.7K
Distribution of Molecular Speeds01:27

Distribution of Molecular Speeds

4.0K
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...
4.0K

You might also read

Related Articles

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

Sort by
Same author

Scalable Boltzmann generators for equilibrium sampling of large-scale materials.

Nature communications·2026
Same author

Assessing generative modeling approaches for free energy estimates in condensed matter.

The Journal of chemical physics·2026
Same author

Accurate Chemistry Collection: Coupled cluster atomization energies for broad chemical space.

Scientific data·2026
Same author

Learning data-efficient coarse-grained molecular dynamics from forces and noise.

Nature communications·2026
Same author

Extending the range of graph neural networks with global encodings.

Nature communications·2026
Same author

Operator forces for coarse-grained molecular dynamics.

The Journal of chemical physics·2025

Related Experiment Video

Updated: Jul 17, 2025

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

1.3K

DeepQMC: An open-source software suite for variational optimization of deep-learning molecular wave functions.

Z Schätzle1, P B Szabó1, M Mezera1

  • 1FU Berlin, Department of Mathematics and Computer Science, Arnimallee 6, Berlin 14195, Germany.

The Journal of Chemical Physics
|September 6, 2023
PubMed
Summary
This summary is machine-generated.

DeepQMC offers a unified software framework for deep learning quantum Monte Carlo methods. This package enhances computational chemistry accuracy and efficiency for molecular systems.

More Related Videos

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

4.5K
Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics
10:52

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics

Published on: April 12, 2019

12.8K

Related Experiment Videos

Last Updated: Jul 17, 2025

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

1.3K
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

4.5K
Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics
10:52

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics

Published on: April 12, 2019

12.8K

Area of Science:

  • Computational Chemistry
  • Quantum Mechanics
  • Machine Learning

Background:

  • Accurate solutions to the electronic Schrödinger equation are crucial in computational chemistry.
  • Quantum Monte Carlo (QMC) methods offer parallelizable and scalable approaches.
  • Machine learning (ML) enhances QMC accuracy through neural network wave function Ansätze.

Purpose of the Study:

  • Introduce DeepQMC, a modular and extendable software package.
  • Unify existing deep learning quantum Monte Carlo architectures.
  • Facilitate the development and adoption of ML-QMC methods.

Main Methods:

  • Variational quantum Monte Carlo (VQMC) in real space.
  • Optimization of neural network wave functions.
  • Development of a unified software framework for ML-QMC.

Main Results:

  • DeepQMC provides a common framework for diverse deep learning QMC architectures.
  • Demonstrates state-of-the-art accuracy on molecular systems.
  • Highlights technical challenges and presents example applications.

Conclusions:

  • DeepQMC aims to make advanced ML-QMC methods accessible.
  • Promotes broader adoption by quantum chemists and machine learning practitioners.
  • Establishes a foundation for future research in the field.