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

Step-Growth Polymerization: Overview01:03

Step-Growth Polymerization: Overview

4.5K
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...
4.5K
Radical Chain-Growth Polymerization: Overview01:10

Radical Chain-Growth Polymerization: Overview

3.5K
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...
3.5K
Radical Chain-Growth Polymerization: Mechanism01:09

Radical Chain-Growth Polymerization: Mechanism

3.6K
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 species into...
3.6K
Ziegler–Natta Chain-Growth Polymerization: Overview01:17

Ziegler–Natta Chain-Growth Polymerization: Overview

4.1K
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...
4.1K
Radical Chain-Growth Polymerization: Chain Branching01:17

Radical Chain-Growth Polymerization: Chain Branching

2.5K
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...
2.5K
Olefin Metathesis Polymerization: Ring-Opening Metathesis Polymerization (ROMP)01:16

Olefin Metathesis Polymerization: Ring-Opening Metathesis Polymerization (ROMP)

3.2K
Ring-opening metathesis polymerization or ROMP involves strained cycloalkenes as starting materials. The mechanism of ROMP proceeds by reacting cycloalkene with Grubbs catalyst to give metallacyclobutane intermediate which undergoes a ring-opening reaction to form new carbene. The new carbene reacts with another molecule of cycloalkene. Repetition of these steps leads to the formation of an unsaturated open-chain polymer product. All these steps are reversible, however, relieving the ring...
3.2K

You might also read

Related Articles

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

Sort by
Same author

Assessing and rationalizing the performance of Hessian update schemes for reaction path Hamiltonian rate calculations.

The Journal of chemical physics·2021
Same author

Solving the Schrödinger equation using program synthesis.

The Journal of chemical physics·2021
Same author

A new diabatization scheme for direct quantum dynamics: Procrustes diabatization.

The Journal of chemical physics·2020
Same author

The role of nuclear quantum effects in the relative stability of hexagonal and cubic ice.

The Journal of chemical physics·2019
Same author

Direct quantum dynamics using variational Gaussian wavepackets and Gaussian process regression.

The Journal of chemical physics·2019
Same author

MCTDH on-the-fly: Efficient grid-based quantum dynamics without pre-computed potential energy surfaces.

The Journal of chemical physics·2018

Related Experiment Video

Updated: Feb 16, 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

8.5K

Accelerated path-integral simulations using ring-polymer interpolation.

Samuel J Buxton1, Scott Habershon1

  • 1Department of Chemistry and Centre for Scientific Computing, University of Warwick, Coventry CV4 7AL, United Kingdom.

The Journal of Chemical Physics
|December 17, 2017
PubMed
Summary
This summary is machine-generated.

A new method called ring-polymer interpolation (RPI) accelerates quantum simulations by reducing computational cost. RPI accurately reproduces results from path-integral simulations with fewer potential energy surface evaluations.

More Related Videos

Depolymerizable Olefinic Polymers Based on Fused-Ring Cyclooctene Monomers
08:12

Depolymerizable Olefinic Polymers Based on Fused-Ring Cyclooctene Monomers

Published on: December 16, 2022

4.0K
Synthesis of Monodisperse Cylindrical Nanoparticles via Crystallization-driven Self-assembly of Biodegradable Block Copolymers
11:42

Synthesis of Monodisperse Cylindrical Nanoparticles via Crystallization-driven Self-assembly of Biodegradable Block Copolymers

Published on: June 20, 2019

8.3K

Related Experiment Videos

Last Updated: Feb 16, 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

8.5K
Depolymerizable Olefinic Polymers Based on Fused-Ring Cyclooctene Monomers
08:12

Depolymerizable Olefinic Polymers Based on Fused-Ring Cyclooctene Monomers

Published on: December 16, 2022

4.0K
Synthesis of Monodisperse Cylindrical Nanoparticles via Crystallization-driven Self-assembly of Biodegradable Block Copolymers
11:42

Synthesis of Monodisperse Cylindrical Nanoparticles via Crystallization-driven Self-assembly of Biodegradable Block Copolymers

Published on: June 20, 2019

8.3K

Area of Science:

  • Computational Chemistry
  • Quantum Mechanics
  • Statistical Mechanics

Background:

  • Imaginary-time path-integral (PI) molecular simulations compute exact quantum statistical mechanical properties.
  • PI simulations are computationally intensive due to repeated potential energy surface (PES) and force evaluations.
  • Existing methods like ring-polymer contraction have limitations, especially with on-the-fly ab initio calculations.

Purpose of the Study:

  • To introduce a novel method, ring-polymer interpolation (RPI), for accelerating PI simulations.
  • To enable large-scale PI simulations using ab initio PESs without prior assumptions.
  • To overcome the computational bottlenecks of current PI simulation acceleration techniques.

Main Methods:

  • Development of the ring-polymer interpolation (RPI) technique.
  • Application of RPI to simulations of liquid water using an empirical PES.
  • Comparison of RPI results with fully-converged PI simulations.

Main Results:

  • RPI significantly reduces the number of PES evaluations required for accurate simulations.
  • RPI accurately reproduces key observables, such as radial distribution functions, in liquid water.
  • The method demonstrates efficiency without compromising simulation accuracy.

Conclusions:

  • Ring-polymer interpolation (RPI) offers an effective way to accelerate path-integral simulations.
  • RPI enables the use of computationally demanding ab initio PESs in large-scale quantum simulations.
  • This method addresses the limitations of previous acceleration techniques for PI simulations.