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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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Step-Growth Polymerization: Overview01:03

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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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相关实验视频

Updated: May 21, 2025

Polymer Microarrays for High Throughput Discovery of Biomaterials
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植入定向聚合物:从噪音图像推断出一个随机步行.

Sun Woo P Kim1, Austen Lamacraft2

  • 1King's College London, Department of Physics, Strand, London WC2R 2LS, United Kingdom.

Physical review. E
|March 19, 2025
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概括
此摘要是机器生成的。

我们介绍了一个植入的定向聚合物模型,用于从噪音数据中推断随机步行者路径. 在凯利树上,发生相位过渡,随着噪声的增加,路径推断变得不可能.

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Synthesis of Cyclic Polymers and Characterization of Their Diffusive Motion in the Melt State at the Single Molecule Level
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科学领域:

  • 统计物理 统计物理
  • 机器学习 机器学习
  • 信息理论 信息理论

背景情况:

  • 定向聚合物模型是统计物理学的基本概念.
  • 贝叶斯推理对于从杂的观测中重建隐藏状态至关重要.
  • 隐藏的马尔科夫模型为顺序数据分析提供了一个框架.

研究的目的:

  • 介绍和分析种植定向聚合物模型.
  • 从噪音图像数据推断随机步行者的行为.
  • 探索隐藏的马尔科夫模型的贝叶斯推理中的相位过渡.

主要方法:

  • 公式作为一个非线性贝叶斯推理问题.
  • 统计物理学中的定向聚合物问题的概括.
  • 为一维步行者进行数值调查和分析论证.
  • 将定向聚合物方法应用于凯利树结构.

主要成果:

  • 对于一个一维的步行者来说,没有观察到相位过渡.
  • 在凯利树上发现了一个相位过渡,信号与噪声比率下降.
  • 在过渡时,推理变得不可能,路径重叠从1下降到0.

结论:

  • 植入定向聚合物模型为隐藏状态推断提供了新的见解.
  • 阶段过渡的存在或不存在取决于底层结构 (1D与凯利树).
  • 信号与噪声比率的下降对路径推断的可靠性产生了重大影响.