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

Theories of Dissolution: The Danckwerts' Model and Interfacial Barrier Model01:09

Theories of Dissolution: The Danckwerts' Model and Interfacial Barrier Model

Various dissolution theories provide insight into the factors that influence the dissolution rate. Danckwerts' Model suggests that turbulence, rather than a stagnant layer, characterizes the dissolution medium at the solid-liquid interface. In this model, the agitated solvent contains macroscopic packets that move to the interface via eddy currents, facilitating the absorption and delivery of the drug to the bulk solution. The regular replenishment of solvent packets maintains the concentration...
Precipitation Processes01:12

Precipitation Processes

The experimental conditions in a gravimetric analysis should be optimized to maximize the particle size and purity of the obtained precipitate. Ideally, the concentration of the precipitating reagent should be low with effective stirring to maintain low relative supersaturation for the growth of large crystals. In homogeneous precipitation, the precipitant is slowly generated by a chemical reaction in the solution to avoid local reagent excesses. For example, urea decomposes gradually to...
Theories of Dissolution: Diffusion Layer Model01:15

Theories of Dissolution: Diffusion Layer Model

Dissolution, the process by which drug particles dissolve in a solvent, is explained by the diffusion layer model, a theoretical framework that simulates the absorption of oral drugs and allows us to analyze experimental data.
This process starts with a thin layer, saturated with the drug, forming at the interface between the solid and liquid. The solute then diffuses from this layer into the main solution. The Noyes-Whitney equation suggests that the rate of dissolution relies on the diffusion...
Recrystallization: Solid–Solution Equilibria01:10

Recrystallization: Solid–Solution Equilibria

Recrystallization is a purification technique used to separate impurities from solid compounds. In this technique, no chemical reactions occur. Instead, it exploits physical properties only, specifically, the solubility differences between the desired compound and impurities, either at a single temperature or at different temperatures, and under other selected conditions. The solid-solution equilibrium (solubility equilibrium) of each component in the solution represents a binary phase...
Design Example: Creating a Hydraulic Model of a Dam Spillway01:21

Design Example: Creating a Hydraulic Model of a Dam Spillway

Scaled hydraulic models of dam spillways provide a practical way to replicate and study the intricate flow dynamics of these structures. Often built to a 1:15 ratio, these models allow for observing critical water behavior, such as velocity distribution, flow patterns, and energy dissipation.
Crystal Growth: Principles of Crystallization01:25

Crystal Growth: Principles of Crystallization

Crystallization is a phase transformation process in which crystals are precipitated from a supersaturated solution or formed from other sources. During crystallization, atoms or molecules arrange themselves into a well-defined, rigid crystal lattice to minimize energy.
Initiating crystallization involves manipulating the concentration of the solute and the temperature of the solution. Since crystal growth occurs when the ratio of concentration and solubility of the solute in the solvent – the...

You might also read

Related Articles

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

Sort by
Same author

Assessment of scoring functions for computational models of protein-protein interfaces.

Physical review. E·2026
Same author

SCUDDO: an unsupervised clustering algorithm for single-cell Hi-C maps using diagonal diffusion operators.

Bioinformatics (Oxford, England)·2026
Same author

Residue burial encodes a protein's fold.

bioRxiv : the preprint server for biology·2026
Same author

Droplet breakup against an isolated obstacle.

Soft matter·2026
Same author

Assessment of scoring functions for computational models of protein-protein interfaces.

ArXiv·2026
Same author

Mechanical plasticity of cell membranes enhances epithelial wound closure.

Physical review research·2025

Related Experiment Video

Updated: Jun 25, 2026

Fluid-cell Raman Spectroscopy for operando Studies of Reaction and Transport Phenomena during Silicate Glass Corrosion
06:48

Fluid-cell Raman Spectroscopy for operando Studies of Reaction and Transport Phenomena during Silicate Glass Corrosion

Published on: May 9, 2025

Percolation model for slow dynamics in glass-forming materials.

Gregg Lois1, Jerzy Blawzdziewicz, Corey S O'Hern

  • 1Department of Physics, Department of Mechanical Engineering, Yale University, New Haven, Connecticut 06520-8284, USA.

Physical Review Letters
|March 5, 2009
PubMed
Summary

We found that the glass transition is linked to percolation in mobility regions. This explains key features of glassy dynamics, like stretched-exponential responses and relaxation times, through critical percolation properties.

More Related Videos

Cooling Rate Dependent Ellipsometry Measurements to Determine the Dynamics of Thin Glassy Films
09:32

Cooling Rate Dependent Ellipsometry Measurements to Determine the Dynamics of Thin Glassy Films

Published on: January 26, 2016

Methods of Ex Situ and In Situ Investigations of Structural Transformations: The Case of Crystallization of Metallic Glasses
08:55

Methods of Ex Situ and In Situ Investigations of Structural Transformations: The Case of Crystallization of Metallic Glasses

Published on: June 7, 2018

Related Experiment Videos

Last Updated: Jun 25, 2026

Fluid-cell Raman Spectroscopy for operando Studies of Reaction and Transport Phenomena during Silicate Glass Corrosion
06:48

Fluid-cell Raman Spectroscopy for operando Studies of Reaction and Transport Phenomena during Silicate Glass Corrosion

Published on: May 9, 2025

Cooling Rate Dependent Ellipsometry Measurements to Determine the Dynamics of Thin Glassy Films
09:32

Cooling Rate Dependent Ellipsometry Measurements to Determine the Dynamics of Thin Glassy Films

Published on: January 26, 2016

Methods of Ex Situ and In Situ Investigations of Structural Transformations: The Case of Crystallization of Metallic Glasses
08:55

Methods of Ex Situ and In Situ Investigations of Structural Transformations: The Case of Crystallization of Metallic Glasses

Published on: June 7, 2018

Area of Science:

  • Physics
  • Materials Science
  • Statistical Mechanics

Background:

  • Glassy dynamics present complex behaviors not fully explained by traditional theories.
  • Understanding the glass transition is crucial for materials science and condensed matter physics.

Purpose of the Study:

  • To establish a connection between the glass transition and percolation phenomena in configuration space.
  • To explain the origins of characteristic features observed in glassy dynamics.

Main Methods:

  • Analysis of configuration space to identify regions of mobility.
  • Application of mean-field percolation theory to model glassy dynamics.
  • Derivation of theoretical predictions for exponents and relaxation times.

Main Results:

  • A direct link between glass transition and percolation of mobile regions was identified.
  • Stretched-exponential response functions and diverging structural relaxation times are shown to be consequences of percolation criticality.
  • The percolation model predicts a specific range for stretching exponents (1/3 ≤ beta ≤ 1).

Conclusions:

  • Mean-field percolation theory provides a unifying framework for understanding glassy dynamics.
  • The model successfully explains key experimental observations and offers testable predictions.
  • This work advances the theoretical understanding of the glass transition and complex dynamics in disordered systems.