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Related Concept Videos

Behavior of Gas Molecules: Molecular Diffusion, Mean Free Path, and Effusion03:48

Behavior of Gas Molecules: Molecular Diffusion, Mean Free Path, and Effusion

Although gaseous molecules travel at tremendous speeds (hundreds of meters per second), they collide with other gaseous molecules and travel in many different directions before reaching the desired target. At room temperature, a gaseous molecule will experience billions of collisions per second. The mean free path is the average distance a molecule travels between collisions. The mean free path increases with decreasing pressure; in general, the mean free path for a gaseous molecule will be...
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Diffusion is a type of passive transport. In passive transport, a substance tends to move from an area of high concentration to an area of low concentration until the concentration is equal across the space. For example, take the diffusion of substances through the air. When someone opens a perfume bottle in a room filled with people, the perfume is at its highest concentration in the bottle and is at its lowest at the edges of the room. The perfume vapor will diffuse, or spread away, from the...
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Diffusion is the passive movement of substances down their concentration gradients—requiring no expenditure of cellular energy. Substances, such as molecules or ions, diffuse from an area of high concentration to an area of low concentration in the cytosol or across membranes. Eventually, the concentration will even out, with the substance moving randomly but causing no net change in concentration. Such a state is called dynamic equilibrium, which is essential for maintaining overall...
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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...
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Related Experiment Video

Updated: Jun 3, 2026

Synthesis of Cyclic Polymers and Characterization of Their Diffusive Motion in the Melt State at the Single Molecule Level
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Synthesis of Cyclic Polymers and Characterization of Their Diffusive Motion in the Melt State at the Single Molecule Level

Published on: September 26, 2016

Thermodynamic driving force for diffusion: comparison between theory and simulation.

Jessica R Whitman1, Gregory L Aranovich, Marc D Donohue

  • 1Department of Chemical & Biomolecular Engineering, The Johns Hopkins University, Baltimore, Maryland 21218, USA. jessica.whitman@jhu.edu

The Journal of Chemical Physics
|March 10, 2011
PubMed
Summary

The impingement rate of diffusing molecules depends on their surroundings' mobility. Molecular dynamics simulations confirmed that changing solvent mobility alters diffusion flux, even when other factors remain constant.

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Area of Science:

  • Condensed matter physics
  • Computational chemistry
  • Materials science

Background:

  • Lattice density functional theory (DFT) equations can be reformulated into a differential form.
  • This reformulation allows for the determination of a property whose gradient is proportional to diffusive flux.
  • For color counter diffusion, this property relates to the impingement rate of species onto vacancies and molecules.

Purpose of the Study:

  • To investigate the relationship between the mobility of the surroundings and the diffusion flux of a species.
  • To validate the finding that the impingement rate of diffusing molecules depends on the mobility of their environment.
  • To determine if altering solvent mobility affects the diffusion flux of a species under controlled conditions.

Main Methods:

  • Molecular dynamics (MD) simulations were employed to study color counter diffusion.
  • The mobility of the solvent was systematically varied during the simulations.
  • Key factors such as density gradient, available volume, and temperature were held constant.

Main Results:

  • The study demonstrated that changes in solvent mobility directly influenced the flux of the diffusing species.
  • This response was observed even when other critical parameters were kept invariant.
  • The findings support the theoretical prediction linking diffusion flux to the mobility of the surrounding medium.

Conclusions:

  • The mobility of the surrounding environment is a critical determinant of diffusion flux.
  • Lattice DFT and MD simulations provide complementary insights into diffusion phenomena.
  • This work highlights the importance of considering local mobility effects in diffusion modeling.