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

Maxwell-Boltzmann Distribution: Problem Solving01:20

Maxwell-Boltzmann Distribution: Problem Solving

2.3K
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
2.3K
The Thermodynamics of Mixing01:28

The Thermodynamics of Mixing

146
Mixing is a fascinating phenomenon in thermodynamics, particularly when considering the Gibbs energy of a mixture at constant temperature and pressure. This energy, denoted as G, tends to decrease during spontaneous mixing processes, offering insights into the composition changes that occur.Imagine two ideal gases, initially separated in different containers, with amounts nA and nB, respectively, both at a temperature T and pressure p. The chemical potentials of these gases have their 'pure'...
146
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
Carrier Transport01:21

Carrier Transport

1.2K
The generation of electrical current in semiconductors is fundamentally driven by two mechanisms: drift and diffusion. These processes are essential for the functionality and performance of semiconductor-based devices.
Drift Current:
The drift of charge carriers is started by an external electric field (E). Charged particles, such as electrons and holes, experience an acceleration between collisions with lattice atoms. For electrons, this results in a drift velocity (vd) given by:
1.2K
Ideal Solutions or Mixtures01:20

Ideal Solutions or Mixtures

123
From a molecular perspective, an ideal solution is one in which the intermolecular interactions between unlike molecules are, on average, the same as those between like molecules. This is the case for ideal gas mixtures, where the molecules are far apart and do not interact with each other. However, for condensed phases like liquids or solids, the molecules are close together and interact with each other. In an ideal solution, the molecules of different species are so similar to each other that...
123
Mixtures of Gases: Dalton's Law of Partial Pressures and Mole Fractions03:03

Mixtures of Gases: Dalton's Law of Partial Pressures and Mole Fractions

35.6K
Unless individual gases chemically react with each other, the individual gases in a mixture of gases do not affect each other’s pressure. Each gas in a mixture exerts the same pressure that it would exert if it were present alone in the container. The pressure exerted by each individual gas in a mixture is called its partial pressure.
35.6K

You might also read

Related Articles

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

Sort by
Same author

Cooling Mechanism Controls Motility-Induced Phase Separation in Inertial Active Liquids.

Physical review letters·2026
Same author

Active Gaussian network model: a non-equilibrium description of protein fluctuations and allosteric behavior.

Physical biology·2025
Same author

A framework for studying oxygen and nitric oxide transport in unstable flow through a patient-based abdominal aortic aneurysm model.

Computer methods in biomechanics and biomedical engineering·2025
Same author

Spontaneous generation of angular momentum in chiral active crystals.

Soft matter·2025
Same author

Fluid flow and amyloid transport and aggregation in the brain interstitial space.

PNAS nexus·2024
Same author

Dynamics and Structures of Amyloid Aggregates under Fluid Flows.

The journal of physical chemistry letters·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: Apr 27, 2026

Analyzing Mixing Inhomogeneity in a Microfluidic Device by Microscale Schlieren Technique
10:12

Analyzing Mixing Inhomogeneity in a Microfluidic Device by Microscale Schlieren Technique

Published on: June 12, 2015

8.7K

Lattice Boltzmann method for mixtures at variable Schmidt number.

Michele Monteferrante1, Simone Melchionna2, Umberto Marini Bettolo Marconi3

  • 1Consiglio Nazionale delle Ricerche, Istituto di Chimica del Riconoscimento Molecolare (ICRM-CNR), Via Mario Bianco, 20131 Milan, Italy.

The Journal of Chemical Physics
|July 10, 2014
PubMed
Summary
This summary is machine-generated.

This study introduces a new Lattice Boltzmann Method approach to precisely control species diffusion in multicomponent mixtures without altering solution viscosity. The method uses distinct timescales for mass and momentum diffusion, enabling effective drag force control between species.

More Related Videos

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids
11:03

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids

Published on: December 4, 2017

7.6K
Thermochemical Studies of NiII and ZnII Ternary Complexes Using Ion Mobility-Mass Spectrometry
16:11

Thermochemical Studies of NiII and ZnII Ternary Complexes Using Ion Mobility-Mass Spectrometry

Published on: June 8, 2022

1.9K

Related Experiment Videos

Last Updated: Apr 27, 2026

Analyzing Mixing Inhomogeneity in a Microfluidic Device by Microscale Schlieren Technique
10:12

Analyzing Mixing Inhomogeneity in a Microfluidic Device by Microscale Schlieren Technique

Published on: June 12, 2015

8.7K
An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids
11:03

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids

Published on: December 4, 2017

7.6K
Thermochemical Studies of NiII and ZnII Ternary Complexes Using Ion Mobility-Mass Spectrometry
16:11

Thermochemical Studies of NiII and ZnII Ternary Complexes Using Ion Mobility-Mass Spectrometry

Published on: June 8, 2022

1.9K

Area of Science:

  • Computational physics
  • Fluid dynamics
  • Chemical engineering

Background:

  • Simulating multicomponent mixtures requires controlling inter-species diffusion while keeping viscosity constant.
  • Existing Lattice Boltzmann Methods face challenges in independently tuning these properties.

Purpose of the Study:

  • To develop a modified Lattice Boltzmann Method for independent control of mutual diffusivity and fixed solution viscosity in multicomponent mixtures.
  • To introduce a tunable drag force between species for diffusivity control.

Main Methods:

  • Modification of multicomponent Bhatnagar-Gross-Krook evolution equations.
  • Introduction of two distinct timescales for mass and momentum diffusion.
  • Numerical simulations of neutral binary and charged ternary mixtures.

Main Results:

  • The modified method successfully controls mutual diffusivity by an effective inter-species drag force.
  • Numerical simulations confirm the method's accuracy for bulk neutral and charged mixtures.
  • Simulations in a charged slit channel show deviations from Helmholtz-Smoluchowski predictions at high diffusivity.

Conclusions:

  • The proposed Lattice Boltzmann Method modification offers precise control over diffusion in multicomponent systems.
  • The method is validated for various mixture types and conditions.
  • Observed deviations at high diffusivity warrant further investigation into electrokinetic phenomena.