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

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

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

2.8K
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...
2.8K
Olefin Metathesis Polymerization: Overview01:13

Olefin Metathesis Polymerization: Overview

2.3K
Recently, the development of olefin metathesis polymerization advanced the field of polymer synthesis. Simply put, the reorganization of substituents on their double bonds between two olefins in the presence of a catalyst is known as the olefin metathesis reaction. The use of metathesis reaction for polymer synthesis is called olefin metathesis polymerization.
Ruthenium-based Grubbs catalyst is the most commonly used catalyst for olefin metathesis polymerization. Grubbs catalyst consists...
2.3K
Step-Growth Polymerization: Overview01:03

Step-Growth Polymerization: Overview

3.7K
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...
3.7K
Ziegler–Natta Chain-Growth Polymerization: Overview01:17

Ziegler–Natta Chain-Growth Polymerization: Overview

3.5K
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...
3.5K
Radical Chain-Growth Polymerization: Overview01:10

Radical Chain-Growth Polymerization: Overview

2.7K
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...
2.7K
Anionic Chain-Growth Polymerization: Overview01:20

Anionic Chain-Growth Polymerization: Overview

2.2K
The polymerization process that involves carbanion as an intermediate is called anionic polymerization. It is also a type of addition or chain-growth polymerization. Anionic polymerization gets initiated by a strong nucleophile such as an organolithium or a Grignard reagent. The most commonly used initiator for anionic polymerization is butyl lithium. Monomers involved in anionic polymerization must possess a vinyl group bonded to one or two electron-withdrawing groups. For instance,...
2.2K

You might also read

Related Articles

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

Sort by
Same author

Nature-Inspired Multi-Level Thresholding Integrated with CNN for Accurate COVID-19 and Lung Disease Classification in Chest X-Ray Images.

Diagnostics (Basel, Switzerland)·2025
Same author

Emulsion-Based Single Drop Generation in a Nonconfined System.

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

Refining COVID-19 Lesion Segmentation in Lung CT Scans Using Swarm Intelligence and Evolutionary Algorithms.

The international journal of medical robotics + computer assisted surgery : MRCAS·2025
Same author

Monitoring Polypropylene Chain-Scission for Dissolution-Based Recycling by In Situ Near Infrared and Raman Spectroscopy.

Macromolecular rapid communications·2025
Same author

Robust Tracking Control of Wheeled Mobile Robot Based on Differential Flatness and Sliding Active Disturbance Rejection Control: Simulations and Experiments.

Sensors (Basel, Switzerland)·2024
Same author

<i>In situ</i> dissolved polypropylene prediction by Raman and ATR-IR spectroscopy for its recycling.

Analytical methods : advancing methods and applications·2024
Same journal

Impact of an Artificial Albumin Corona on Surface Charge-Driven Nano-Bio Interactions and Cytotoxicity of Silver Nanoparticles.

ACS omega·2026
Same journal

Structural and Functional Disruption of Thiopurine S‑Methyltransferase by the A80P Variant: A Simulation and Genotyping Study.

ACS omega·2026
Same journal

CRISPR/Cas12a2-Mediated Ultrasensitive Assay for Rapid Detection of H1N1 Influenza Virus RNA.

ACS omega·2026
Same journal

Photocatalytic Treatment of Real Sugar Industry Wastewater Using Lignocellulosic Biomass-Derived Hydrochar/g-CN.

ACS omega·2026
Same journal

Electrochemical Dopamine Biosensor Based on Plant-Derived Peroxidase Immobilized on Titanate Nanowires.

ACS omega·2026
Same journal

Revealing the Effects of Process Parameters on Structural, Thermal, Mechanical, Biodegradation, and Biocompatibility Properties on the Electrospinning of Poly(vinyl alcohol)/Microbial Inulin Nanofibers.

ACS omega·2026
See all related articles

Related Experiment Video

Updated: Oct 1, 2025

Controlled Photoredox Ring-Opening Polymerization of O-Carboxyanhydrides Mediated by Ni/Zn Complexes
05:48

Controlled Photoredox Ring-Opening Polymerization of O-Carboxyanhydrides Mediated by Ni/Zn Complexes

Published on: November 21, 2017

8.2K

Model Predictive Control with Integrated Model Reduction for a Continuous Lactide Ring-Opening Polymerization

Nawel Afsi1,2, Sami Othman1, Toufik Bakir3

  • 1LAGEPP, University Claude Bernard Lyon1, University of Lyon, Lyon F-69622, France.

ACS Omega
|March 7, 2022
PubMed
Summary
This summary is machine-generated.

Linear model predictive control (LMPC) optimizes poly(lactic acid) production. This biodegradable polymer process benefits from LMPC’s faster recovery from disturbances, outperforming other control methods.

More Related Videos

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

7.9K
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

3.4K

Related Experiment Videos

Last Updated: Oct 1, 2025

Controlled Photoredox Ring-Opening Polymerization of O-Carboxyanhydrides Mediated by Ni/Zn Complexes
05:48

Controlled Photoredox Ring-Opening Polymerization of O-Carboxyanhydrides Mediated by Ni/Zn Complexes

Published on: November 21, 2017

8.2K
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

7.9K
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

3.4K

Area of Science:

  • Polymer Chemistry
  • Chemical Engineering
  • Control Systems

Background:

  • Poly(lactic acid) (PLA) production is gaining importance due to its biodegradability and renewable origins.
  • PLA synthesis is sensitive to operating conditions and raw material impurities, affecting reaction rates and polymer quality.
  • The multivariable and coupled nature of PLA production necessitates advanced control strategies.

Purpose of the Study:

  • To develop and validate a linear model predictive control (LMPC) strategy for poly(lactic acid) production.
  • To implement a model reduction technique for approximating the nonlinear system dynamics, reducing computational load.
  • To compare the performance of LMPC against traditional proportional-integral (PI) control and nonlinear model predictive control (NMPC).

Main Methods:

  • A model reduction technique was applied to linearize the nonlinear PLA production system around an operating point.
  • Linear Model Predictive Control (LMPC) was designed based on the reduced-order linear model.
  • Simulations were conducted to evaluate LMPC performance against PI and NMPC under various conditions, including feed disturbances.

Main Results:

  • LMPC demonstrated superior performance in minimizing off-spec time when feed disturbances occurred.
  • The LMPC approach proved more effective in restoring target production conditions rapidly after disturbances.
  • Compared to PI and NMPC, LMPC offered a better balance of control effectiveness and computational efficiency.

Conclusions:

  • LMPC is a highly effective control strategy for poly(lactic acid) production, enhancing process stability and product quality.
  • Model reduction is a viable method for simplifying complex nonlinear systems for LMPC implementation.
  • LMPC offers significant advantages over conventional control methods for managing disturbances in biopolymer manufacturing.