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Molecular Weight of Step-Growth Polymers01:08

Molecular Weight of Step-Growth Polymers

2.5K
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...
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Polymers: Molecular Weight Distribution01:10

Polymers: Molecular Weight Distribution

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For any given polymer, the weight average molecular weight (Mw) is higher than, if not equal to, the number average molecular weight (Mn). The only situation in which the weight average molecular weight and the number average molecular weight are equal is when a polymer consists only of chains with equal molecular weight. However, this never happens in a synthetic polymer, since it is difficult to control the polymerization process up to a molecular level with accuracy to a hundred percent.
4.1K
Step-Growth Polymerization: Overview01:03

Step-Growth Polymerization: Overview

3.9K
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...
3.9K
Olefin Metathesis Polymerization: Acyclic Diene Metathesis (ADMET)00:53

Olefin Metathesis Polymerization: Acyclic Diene Metathesis (ADMET)

2.0K
Acyclic diene metathesis polymerization or ADMET polymerization involves cross-metathesis of terminal dienes, such as 1,8-nonadiene, to give linear unsaturated polymer and ethylene. As ADMET is a reversible process, the formed ethylene gas must be removed from the reaction mixture to complete the polymerization process.
Similar to cross-metathesis, ADMET also involves the formation of metallacyclobutane intermediate by [2+2] cycloaddition of one of the double bonds of a terminal diene with...
2.0K
Polymers: Defining Molecular Weight01:01

Polymers: Defining Molecular Weight

3.4K
Unlike small molecules with definite molecular weights, polymers are a mixture of individual polymer chains of varying lengths, each with a unique molecular weight.  So, the molecular weight of a polymer is expressed as an average value based on the average size of the polymer chains. The two most common forms of averages used for polymers are the number average molecular weight and weight average molecular weight.
The number average molecular weight (Mn) is the summation of the number...
3.4K
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

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Related Experiment Video

Updated: Oct 31, 2025

Synthesis of Programmable Main-chain Liquid-crystalline Elastomers Using a Two-stage Thiol-acrylate Reaction
11:17

Synthesis of Programmable Main-chain Liquid-crystalline Elastomers Using a Two-stage Thiol-acrylate Reaction

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Controlling Polymer Molecular Weight Distribution through a Latent Mediator Strategy with Temporal Programming.

Miao Chen1, Jiajia Li1, Kaiqi Ma2

  • 1State and Local Joint Engineering Laboratory for Novel Functional Polymeric Materials, Jiangsu Key Laboratory of Advanced Functional Polymer Design and Application, Department of Polymer Science and Engineering, College of Chemistry, Chemical Engineering and Materials Science, Soochow University, Suzhou, 215123, China.

Angewandte Chemie (International Ed. in English)
|June 30, 2021
PubMed
Summary

Researchers developed a new method to precisely control polymer molecular weight distribution (MWD) in cationic polymerization using light-activated mediators and temporal programming, enabling tailored polymer architectures.

Keywords:
latent mediatorsliving cationic polymerizationmolecular weight distributiontemporal programming

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Area of Science:

  • Polymer Chemistry
  • Materials Science

Background:

  • Polymer molecular weight distribution (MWD) is a critical characteristic influencing material properties.
  • Precise control over MWD remains a challenge in controlled polymerization techniques.

Purpose of the Study:

  • To present a robust method for controlling polymer MWD in controlled cationic polymerizations.
  • To demonstrate the ability to tune MWD breadth and shape using temporal programming and light.

Main Methods:

  • A latent mediator strategy was employed, combined with temporal programming to regenerate mediators dynamically.
  • An external light source was used to control mediator regeneration, allowing for precise temporal adjustments.
  • Bimodal, trimodal, and tetramodal MWDs were synthesized by adjusting light exposure over time.

Main Results:

  • The method successfully controlled polymer MWD, achieving breadths ranging from 1.06 to 2.09.
  • Various MWD shapes, including bimodal, trimodal, and tetramodal distributions, were obtained.
  • Polymers exhibited good chain end fidelity, confirmed by successful chain-extension experiments.

Conclusions:

  • This light-controlled temporal programming approach offers versatile MWD control in cationic polymerization.
  • The technique allows for the synthesis of polymers with tailored molecular architectures.
  • Integration with AI offers future potential for automated polymer synthesis.