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...
Ziegler–Natta Chain-Growth Polymerization: Overview01:17

Ziegler–Natta Chain-Growth Polymerization: Overview

Ziegler–Natta polymerization is another form of addition or chain‐growth polymerization used for synthesizing linear polymers over branched polymers. The catalyst used for polymerization is the Ziegler–Natta catalyst, named after Karl Ziegler and Giulio Natta, who developed it in 1953. This catalyst is an organometallic complex of titanium tetrachloride and triethyl aluminum, with the active form of the catalyst being an alkyl titanium compound. Using the Ziegler–Natta catalyst, high molecular...
Anionic Chain-Growth Polymerization: Mechanism01:04

Anionic Chain-Growth Polymerization: Mechanism

The mechanism for anionic chain-growth polymerization involves initiation, propagation, and termination steps. In the initiation step, a nucleophilic anion, such as butyl lithium, initiates the polymerization process by attacking the π bond of the vinylic monomer. As a result, a carbanion, stabilized by the electron‐withdrawing group, is generated. The resulting carbanion acts as a Michael donor in the propagation step and attacks the second vinylic monomer, which acts as a Michael acceptor.
The Fluid Mosaic Model01:34

The Fluid Mosaic Model

The fluid mosaic model was first proposed as a visual representation of research observations. The model comprises the composition and dynamics of membranes and serves as a foundation for future membrane-related studies. The model depicts the structure of the plasma membrane with a variety of components, which include phospholipids, proteins, and carbohydrates. These integral molecules are loosely bound, defining the cell’s border and providing fluidity for optimal function.
Step-Growth Polymerization: Overview01:03

Step-Growth Polymerization: Overview

Step-growth or condensation polymerization is a stepwise reaction of bi or multifunctional monomers to form long-chain polymers. As all the monomers are reactive, most of the monomers are consumed at the early stages of the reaction to form small chains of reactive oligomers, which then combine to form long polymer chains in the late stages. Hence, the reaction has to proceed for a long time to achieve high molecular weight polymers.
Many natural and synthetic polymers are produced by...
Cationic Chain-Growth Polymerization: Mechanism00:57

Cationic Chain-Growth Polymerization: Mechanism

The cationic polymerization mechanism consists of three steps: initiation, propagation, and termination. In the initiation step of the polymerization process, the π bond of a monomer gets protonated by the Lewis acid catalyst, which is formed from boron trifluoride and water. The protonation of the π bond generates a carbocation stabilized by the electron‐donating group. In the propagation step, the π bond of the second monomer acts as a nucleophile and attacks the generated carbocation,...

You might also read

Related Articles

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

Sort by
Same author

Crystallite Rotation Drives Strain Softening in Semicrystalline Polyethylene.

ACS materials Au·2026
Same author

The importance of sub-nanosecond relaxations on the ballistic impact resistance of cross-linked thermoset network polymers.

Soft matter·2026
Same author

General inverse-cube thickness scaling of projectile penetration energy in ultrathin films.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

Ionic Selectivity of NaCl Solutions in Graphene-Based Single-Digit Nanopores.

Langmuir : the ACS journal of surfaces and colloids·2026
Same author

Geometric indicators of local plasticity in glasses measured by scanning small-beam diffraction.

Acta crystallographica. Section A, Foundations and advances·2025
Same author

Confined active particles: wall accumulation and correspondence between active and fluid systems.

Soft matter·2025

Related Experiment Video

Updated: May 23, 2026

Synthesis of Cyclic Polymers and Characterization of Their Diffusive Motion in the Melt State at the Single Molecule Level
06:55

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

Published on: September 26, 2016

An enhanced entangled polymer model for dissipative particle dynamics.

Timothy W Sirk1, Yelena R Slizoberg, John K Brennan

  • 1Macromolecular Science and Technology Branch, Army Research Laboratory, Aberdeen, Maryland, USA.

The Journal of Chemical Physics
|April 10, 2012
PubMed
Summary

This study introduces a new polymer model for dissipative particle dynamics (DPD) simulations. The modified segmental repulsive potential (mSRP) effectively captures polymer entanglements, improving structural and thermodynamic predictions.

More Related Videos

Confocal Imaging of Confined Quiescent and Flowing Colloid-polymer Mixtures
10:56

Confocal Imaging of Confined Quiescent and Flowing Colloid-polymer Mixtures

Published on: May 20, 2014

Molecular Entanglement and Electrospinnability of Biopolymers
07:59

Molecular Entanglement and Electrospinnability of Biopolymers

Published on: September 3, 2014

Related Experiment Videos

Last Updated: May 23, 2026

Synthesis of Cyclic Polymers and Characterization of Their Diffusive Motion in the Melt State at the Single Molecule Level
06:55

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

Published on: September 26, 2016

Confocal Imaging of Confined Quiescent and Flowing Colloid-polymer Mixtures
10:56

Confocal Imaging of Confined Quiescent and Flowing Colloid-polymer Mixtures

Published on: May 20, 2014

Molecular Entanglement and Electrospinnability of Biopolymers
07:59

Molecular Entanglement and Electrospinnability of Biopolymers

Published on: September 3, 2014

Area of Science:

  • Computational physics
  • Polymer science
  • Soft matter physics

Background:

  • Dissipative Particle Dynamics (DPD) is a mesoscale simulation technique.
  • Standard DPD models often struggle to accurately represent polymer entanglements.
  • Accurate modeling of entanglements is crucial for predicting polymer melt properties.

Purpose of the Study:

  • To develop an improved polymer model within the DPD framework.
  • To enhance the capture of polymer entanglements using modified repulsive interactions.
  • To validate the new model's ability to reproduce structural and thermodynamic properties.

Main Methods:

  • Development of a modified segmental repulsive potential (mSRP).
  • Utilizing simplified bond-bond repulsive interactions to prevent bond crossings.
  • Parameter determination based on topological, structural, and thermodynamic considerations.
  • Calculation of diffusion and mechanical properties for validation.

Main Results:

  • The mSRP model successfully captures polymer entanglements.
  • Structural and thermodynamic properties are improved compared to standard DPD.
  • The mSRP produces chain structures and thermodynamic behavior similar to standard DPD flexible chains.
  • Diffusion and mechanical properties of entangled melts were accurately predicted.

Conclusions:

  • The mSRP offers a robust alternative for modeling polymer entanglements in DPD.
  • This approach enhances the predictive power of DPD for complex polymer systems.
  • The developed model provides a valuable tool for simulating entangled polymer melts.