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Related Concept Videos

Step-Growth Polymerization: Overview01:03

Step-Growth Polymerization: Overview

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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...
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Cationic Chain-Growth Polymerization: Mechanism00:57

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

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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...
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Polymers02:34

Polymers

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The word polymer is derived from the Greek words “poly” which means “many” and “mer” which means “parts”. Polymers are long chains of molecules composed of repeating units of smaller molecules, known as monomers. They either occur naturally, such as DNA and proteins, or can be constructed synthetically, like plastics. They have varied structural characteristics, such as linear chains, branched chains, or complex networks, that contribute to the...
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Anionic Chain-Growth Polymerization: Overview01:20

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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,...
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Anionic Chain-Growth Polymerization: Mechanism01:04

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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...
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Electrochemical Preparation of Poly3,4-Ethylenedioxythiophene Layers on Gold Microelectrodes for Uric Acid-Sensing Applications
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An Informatics Approach for Designing Conducting Polymers.

Harikrishna Sahu1, Hongmo Li1, Lihua Chen1

  • 1Department of Materials Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States.

ACS Applied Materials & Interfaces
|May 26, 2021
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Summary

Researchers developed predictive models to screen over 800,000 polymer-dopant combinations for organic electronics. This accelerates the discovery of high-conductivity materials for next-generation devices.

Keywords:
conducting polymerdesign guidelinesmachine learningorganic electronicsvirtual screening

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Area of Science:

  • Materials Science
  • Organic Electronics
  • Computational Chemistry

Background:

  • Doping conjugated polymers is key to enhancing their electrical conductivity for organic electronics.
  • The vast chemical space makes identifying optimal polymer-dopant combinations challenging.

Purpose of the Study:

  • To develop high-performance surrogate models for predicting p-type electrical conductivity.
  • To screen a large dataset of hypothetical polymer-dopant combinations.
  • To identify promising candidates for synthesis and device fabrication.

Main Methods:

  • Training surrogate models on experimentally measured data.
  • Screening over 800,000 polymer-dopant combinations using predictive models.
  • Extracting design guidelines from model predictions.

Main Results:

  • Identification of promising polymer-dopant candidates for high conductivity.
  • Discovery of new design guidelines correlating molecular fragments with conductivity.
  • Development of publicly accessible conductivity prediction models.

Conclusions:

  • Predictive modeling significantly accelerates the search for high-performance organic electronic materials.
  • The developed models and guidelines advance the design principles for conductive polymers.
  • Open-access tools facilitate community-driven innovation in organic electronics.