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

Radical Chain-Growth Polymerization: Overview01:10

Radical Chain-Growth Polymerization: Overview

2.4K
Chain-growth or addition polymerization is successive addition reactions of monomers with a polymer chain. In radical chain-growth polymerization, the reaction proceeds via a free-radical intermediate. The free radical is formed from radical initiators, which spontaneously generate free radicals by homolytic fission. Organic peroxides (such as dibenzoyl peroxide, as shown in Figure 1) or azo compounds are popular radical initiators. A low concentration ratio of radical initiator to monomer is...
2.4K
Radical Chain-Growth Polymerization: Mechanism01:09

Radical Chain-Growth Polymerization: Mechanism

2.5K
The radical chain-growth polymerization mechanism consists of three steps: initiation, propagation, and termination of polymerization. The polymerization initiates when a free radical generated from the radical initiator adds to the unsaturated bond in the monomer. The unpaired electron of the free radical and one π electron in the unsaturated bond creates a σ bond between the free radical and the monomer. As a result, the other π electron in the unsaturated bond converts this...
2.5K
Radical Chain-Growth Polymerization: Chain Branching01:17

Radical Chain-Growth Polymerization: Chain Branching

1.9K
The skeletal structure of polymers synthesized via radical polymerization is always branched. For example, the polymerization of ethylene by radical polymerization results in a low-density grade of polyethylene with a heavily branched skeletal structure. Here, the radical site abstracts hydrogen from the growing chain, and the radical site shifts from the end (a primary carbon center) to anywhere within the growing chain (a secondary carbon center). Consequently, the part of the chain from the...
1.9K
Step-Growth Polymerization: Overview01:03

Step-Growth Polymerization: Overview

3.4K
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...
3.4K
Molecular Weight of Step-Growth Polymers01:08

Molecular Weight of Step-Growth Polymers

2.2K
Step growth polymerization involves bi or multifunctional monomers. Bifunctional monomers react to form linear step growth polymers, whereas multifunctional monomers react to form non-linear or branched polymers.
As the step-growth polymerization involves step-wise condensation of monomers, the molecular weight also builds up eventually. Consequently, high molecular weight polymers are obtained at the late stages of the polymerization, where 99% of monomers have been consumed.
The extent of the...
2.2K
Ziegler–Natta Chain-Growth Polymerization: Overview01:17

Ziegler–Natta Chain-Growth Polymerization: Overview

3.2K
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...
3.2K

You might also read

Related Articles

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

Sort by
Same author

Elucidating and Mitigating Instabilities of Poly(vinyl alcohol) Thin Films in Aqueous Environments.

Langmuir : the ACS journal of surfaces and colloids·2025
Same author

A triangular model of fractal growth with application to adsorptive spin-coating of polymers.

PloS one·2024
Same author

New Insights into Spin Coating of Polymer Thin Films in Both Wetting and Nonwetting Regimes.

Langmuir : the ACS journal of surfaces and colloids·2022
Same author

Using A Spin-Coater to Capture Adhesive Species during Polydopamine Thin-Film Fabrication.

Langmuir : the ACS journal of surfaces and colloids·2019
Same author

Adsorptive Spin Coating To Study Thin-Film Stability in Both Wetting and Nonwetting Regimes.

Langmuir : the ACS journal of surfaces and colloids·2019

Related Experiment Video

Updated: Jun 11, 2025

Scalable Nanohelices for Predictive Studies and Enhanced 3D Visualization
08:03

Scalable Nanohelices for Predictive Studies and Enhanced 3D Visualization

Published on: November 12, 2014

10.4K

Simulation of Polymer Fractal Formation Using a Triangular Network Growth Model.

Kenneth Mulder1,2, Hannah Heierhoff1, Sophia M Lee3

  • 1Department of Mathematics and Statistics, Mount Holyoke College, South Hadley, Massachusetts 01075, United States.

Langmuir : the ACS Journal of Surfaces and Colloids
|September 28, 2024
PubMed
Summary
This summary is machine-generated.

This study models fractal formation in spin-coated polymers using a novel triangular network model. The model accurately simulates polymer aggregation under various conditions, enhancing predictability of thin-film structures.

More Related Videos

Generating a Fractal Microstructure of Laminin-111 to Signal to Cells
06:56

Generating a Fractal Microstructure of Laminin-111 to Signal to Cells

Published on: September 28, 2020

991
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

7.8K

Related Experiment Videos

Last Updated: Jun 11, 2025

Scalable Nanohelices for Predictive Studies and Enhanced 3D Visualization
08:03

Scalable Nanohelices for Predictive Studies and Enhanced 3D Visualization

Published on: November 12, 2014

10.4K
Generating a Fractal Microstructure of Laminin-111 to Signal to Cells
06:56

Generating a Fractal Microstructure of Laminin-111 to Signal to Cells

Published on: September 28, 2020

991
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

7.8K

Area of Science:

  • Polymer Science
  • Materials Science
  • Complex Systems

Background:

  • Fractal formation in spin-coated thin-film polymers is crucial for understanding polymer aggregation and thin-film structure predictability.
  • Existing models often lack interpretable parameters or broad applicability to diverse experimental conditions.

Purpose of the Study:

  • To adapt and apply a novel fractal growth model to simulate spin-coated poly(vinyl alcohol) thin films.
  • To establish clear links between model parameters and polymer aggregation dynamics.
  • To demonstrate the model's versatility across varied experimental parameters and conditions.

Main Methods:

  • Utilized a spreading and contracting triangular network model for fractal growth simulation.
  • Applied the model to poly(vinyl alcohol) on polydimethylsiloxane substrates.
  • Investigated the impact of polymer hydrolysis, spin-coating parameters, and solvent annealing on fractal patterns.

Main Results:

  • Successfully connected model parameters to polymer aggregation processes.
  • Demonstrated accurate simulation of fractal formation under diverse conditions, including varying hydrolysis, spin-coating, and drying.
  • Showcased the model's ability to replicate unique experimental settings and generate novel fractal patterns.

Conclusions:

  • The adapted triangular network model provides a powerful and interpretable tool for studying fractal formation in spin-coated polymers.
  • The model enhances the predictability of thin-film structures by accurately simulating polymer aggregation dynamics.
  • This approach offers a versatile framework for exploring and controlling fractal morphology in polymer thin films.