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Entropy02:39

Entropy

36.8K
Salt particles that have dissolved in water never spontaneously come back together in solution to reform solid particles. Moreover, a gas that has expanded in a vacuum remains dispersed and never spontaneously reassembles. The unidirectional nature of these phenomena is the result of a thermodynamic state function called entropy (S). Entropy is the measure of the extent to which the energy is dispersed throughout a system, or in other words, it is proportional to the degree of disorder of a...
36.8K
Carrier Transport01:21

Carrier Transport

1.0K
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:
1.0K
Diffusion on Chromatography Columns01:07

Diffusion on Chromatography Columns

1.4K
In column chromatography, when an analyte is introduced as a narrow band at the top of the column, the solutes begin to separate and broaden, developing a Gaussian profile. This broadening occurs due to various factors, such as longitudinal diffusion.
Longitudinal diffusion occurs when the solute molecules in the mobile phase diffuse from the more concentrated center of the chromatographic band to the more dilute regions on either side, both towards and against the flow direction. This...
1.4K
Protein Diffusion in the Membrane01:24

Protein Diffusion in the Membrane

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Proteins show rotational as well as lateral diffusion across the membrane. The lateral diffusion of proteins was confirmed through the cell fusion experiment where mouse and human cells were fused, resulting in hybrid cells. When the human and mouse cells fused, the specific membrane proteins on human and mouse cells were marked with the red and green-fluorescent markers, respectively. Initially, the red and green fluorescence was located on the respective hemisphere of the cell. As time...
6.0K
Distribution of Molecular Speeds01:27

Distribution of Molecular Speeds

5.7K
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...
5.7K
Maxwell-Boltzmann Distribution: Problem Solving01:20

Maxwell-Boltzmann Distribution: Problem Solving

3.0K
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
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Related Experiment Video

Updated: Feb 26, 2026

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

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Non-Gaussian Brownian Diffusion in Dynamically Disordered Thermal Environments.

Neha Tyagi1, Binny J Cherayil1

  • 1Dept. of Inorganic and Physical Chemistry, Indian Institute of Science , Bangalore 560012, India.

The Journal of Physical Chemistry. B
|July 19, 2017
PubMed
Summary
This summary is machine-generated.

This study offers simpler methods for analyzing non-Gaussian Brownian diffusion. It confirms that particles can exhibit random walks even with non-Gaussian displacements, identifying new processes with similar anomalous diffusion behaviors.

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Area of Science:

  • Statistical Physics
  • Complex Systems

Background:

  • Brownian diffusion typically follows Gaussian statistics.
  • Non-Gaussian diffusion models are crucial for understanding complex systems.
  • Previous studies explored Ornstein-Uhlenbeck modulated white noise for non-Gaussian diffusion.

Purpose of the Study:

  • To propose simpler analytical methods for non-Gaussian Brownian diffusion.
  • To validate and extend findings on random walks in non-Gaussian systems.
  • To identify novel stochastic processes exhibiting anomalous Brownian behavior.

Main Methods:

  • Analysis of particle dynamics governed by modulated white noise.
  • Development of alternative theoretical treatments for non-Gaussian diffusion models.
  • Investigation of stochastic processes with exponentially decaying time correlations.

Main Results:

  • Substantiated existing findings on non-Gaussian Brownian motion.
  • Identified two-state white noise as a process exhibiting anomalous Brownian behavior.
  • Demonstrated that modulation by exponentially decaying processes leads to similar diffusion.

Conclusions:

  • Simpler methods can effectively treat non-Gaussian diffusion.
  • Anomalous Brownian behavior is not limited to specific noise models.
  • Widespread occurrence of anomalous diffusion is suggested by exponential correlation decay.