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相关概念视频

Molecular Weight of Step-Growth Polymers01:08

Molecular Weight of Step-Growth Polymers

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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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Characteristics and Nomenclature of Copolymers01:24

Characteristics and Nomenclature of Copolymers

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Copolymers are the products obtained from the polymerization of multiple monomer species. So, in a polymer chain itself, there can be multiple repeating units that come from different monomers. The process of synthesizing a polymer from different monomer species is called copolymerization. When two monomers are involved, the polymer is known as a bipolymer. Polymers with three and four monomers are termed terpolymers and quaterpolymers, respectively. Figure 1 depicts the copolymerization of...
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Polymer Classification: Crystallinity01:21

Polymer Classification: Crystallinity

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Unlike ionic or small covalent molecules, polymers do not form crystalline solids due to the diffusion limitations of their long-chain structures. However, polymers contain microscopic crystalline domains separated by amorphous domains.
Crystalline domains are the regions where polymer chains are aligned in an orderly manner and held together in proximity by intermolecular forces. For example, chains in the crystalline domains of polyethylene and nylon are bound together by van der Waals...
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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

Cationic Chain-Growth Polymerization: Mechanism

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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...
2.3K
Polymers02:34

Polymers

35.1K
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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相关实验视频

Updated: Jun 7, 2025

Synthesis of Monodisperse Cylindrical Nanoparticles via Crystallization-driven Self-assembly of Biodegradable Block Copolymers
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在区块聚合物中的计算阶段发现.

Kevin D Dorfman1

  • 1Department of Chemical Engineering and Materials Science, University of Minnesota-Twin Cities, 421 Washington Avenue SE, Minneapolis, Minnesota 55455, United States.

ACS macro letters
|November 12, 2024
PubMed
概括
此摘要是机器生成的。

自相一致的场理论 (SCFT) 对聚合物热力学至关重要,但由于复杂的方程,它在相发现方面扎. 最近的机器学习应用正在将SCFT转化为发现新聚合物相的强大工具.

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科学领域:

  • 聚合物热力学 聚合物热力学
  • 材料科学 材料科学 材料科学

背景情况:

  • 自相一致的场理论 (SCFT) 是聚合物热力学中一个关键的平均场理论.
  • 在区块共聚合物和混合物中理解有序状态时,SCFT是有效的.
  • 解决SCFT用于相位发现的非线性方程具有挑战性,通常需要准确的初步猜测.

研究的目的:

  • 提供SCFT中用于聚合物相位发现的机器学习应用的概述.
  • 解决传统的SCFT在探索新材料阶段的局限性.
  • 要突出SCFT从解释性工具转变为预测工具的转变.

主要方法:

  • 最近用于SCFT的机器学习 (ML) 方法的概述.
  • 对SCFT的粒子群优化 (PSO) 的讨论.
  • 在SCFT中探索贝叶斯优化和生成对抗网络 (GAN).

主要成果:

  • 机器学习方法在克服SCFT融合挑战方面取得了初步成功.
  • ML促进了SCFT的使用,用于在聚合物中实现自动化相位发现.
  • 这些方法为SCFT在材料设计中的更广泛应用铺平了道路.

结论:

  • 机器学习正在使SCFT更容易被用于发现新型聚合物相.
  • 机器学习的整合将SCFT转化为材料科学的更积极的工具.
  • 未来的工作可能将集中在改进ML算法以提高SCFT性能.