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相关概念视频

Polymer Classification: Architecture01:14

Polymer Classification: Architecture

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Polymers are classified as linear or branched on the basis of their chain architecture. The polymer chains in linear polymers have a long chain-like structure with minimal to no branching at all. Even if a polymer features large substituent groups on the monomer, which appear as branches to the skeleton, it is not considered a branched polymer. A branched polymer contains secondary polymer chains that arise from the main polymer chain. The branching occurs when the polymer growth shifts from...
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Polymer Classification: Stereospecificity01:26

Polymer Classification: Stereospecificity

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Polymerization generates chiral centers along the entire backbone of a polymer chain. Accordingly, the stereochemistry of the substituent group has a significant effect on polymer properties. Polymers formed from monosubstituted alkene monomers feature chiral carbons at every alternate position in the polymer backbone. Relative to the predominant orientation of substituents at the adjacent chiral carbons, the polymer can exist in three different configurations: isotactic, syndiotactic, and...
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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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VSEPR Theory02:37

VSEPR Theory

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Valence shell electron-pair repulsion theory (VSEPR theory) enables us to predict the molecular structure around a central atom from an examination of the number of bonds and lone electron pairs in its Lewis structure. The VSEPR model assumes that electron pairs in the valence shell of a central atom will adopt an arrangement that minimizes repulsions between these electron pairs by maximizing the distance between them. The electrons in the valence shell of a central atom form either bonding...
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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.
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Protein Organization01:24

Protein Organization

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Proteins are polymers of amino acid residues. They are versatile and responsible for different cellular functions, including DNA replication, molecular transport, catalysis, and structural support. Proteins have a hierarchical structure comprising at least three levels of organization: primary, secondary, and tertiary structure. Some large proteins have a quaternary structure where individual protein subunits are linked together.
The primary structure of a protein is its amino acid sequence....
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大智慧:一个拓意识的查询语言和子结构搜索算法,用于聚合物化学结构.

Nathan J Rebello1, Tzyy-Shyang Lin1, Heeba Nazeer2

  • 1Department of Chemical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States.

Journal of chemical information and modeling
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概括

一个新的聚合物搜索算法和BigSMARTS查询语言使精确的分子结构识别成为可能. 这通过准确地捕捉聚合物连接和拓学来推进化学数据的可访问性和创新.

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Construction and Systematical Symmetric Studies of a Series of Supramolecular Clusters with Binary or Ternary Ammonium Triphenylacetates
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A Protocol for Computer-Based Protein Structure and Function Prediction
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科学领域:

  • 聚合物化学 聚合物化学
  • 计算化学是一种计算化学.
  • 化学信息学 化学信息学

背景情况:

  • 分子搜索对于化学和生物学中的数据发现至关重要.
  • 目前的聚合物搜索方法有限,依赖于广义名称或不完整的亚结构匹配.
  • 现有的方法缺乏对聚合物连接性和拓学的认识.

研究的目的:

  • 引入一种新的查询语言和搜索算法,用于全面识别聚合物结构.
  • 能够在复杂的聚合物架构中精确地定位单体和功能组.
  • 提高化学数据的可查,可访问性,互操作性和可重复使用性 (FAIR).

主要方法:

  • 开发了BigSMARTS,这是SMARTS的扩展,用于详细的聚合物查询.
  • 实现了一个使用聚合物生成函数的图形横向搜索算法.
  • 算法识别单体,末端组,并执行深度首次搜索子图匹配.

主要成果:

  • 通过对各种聚合物化学和拓学的广泛测试来验证算法.
  • 证明了完全捕捉化学结构的能力,包括单体连接和拓.
  • 处理了大约44万个查询-目标对.

结论:

  • 大SMARTS查询语言和新的算法提供了第一个完整的聚合物结构搜索功能.
  • 该工具增强了聚合物数据分析,并促进了知识发现.
  • 该算法适合在搜索引擎中实现,以改善聚合物数据检索.