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相关概念视频

Polymer Classification: Crystallinity01:21

Polymer Classification: Crystallinity

2.8K
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...
2.8K
Bias01:22

Bias

3.7K
Bias refers to any tendency that prevents a question from being considered unprejudiced. In research, bias occurs when one outcome or answer is selected or encouraged over others in sampling or testing. Bias can occur during any research phase, including study design, data collection, analysis, and publication.
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
3.7K
Intermolecular vs Intramolecular Forces03:00

Intermolecular vs Intramolecular Forces

86.6K
Intermolecular forces (IMF) are electrostatic attractions arising from charge-charge interactions between molecules. The strength of the intermolecular force is influenced by the distance of separation between molecules. The forces significantly affect the interactions in solids and liquids, where the molecules are close together. In gases, IMFs become important only under high-pressure conditions (due to the proximity of gas molecules). Intermolecular forces dictate the physical properties of...
86.6K
Characteristics of Fluids01:31

Characteristics of Fluids

277
Fluids differ from solids primarily in their molecular structure and stress response. Solids have tightly packed molecules with strong intermolecular forces, maintaining their shape and resisting deformation. In contrast, fluids have molecules spaced farther apart with weaker forces, allowing them to flow and deform easily.
Fluids, which include both liquids and gases, are substances that deform continuously under shearing stress. For example, water and oil are liquids with molecules that can...
277
Molecular Comparison of Gases, Liquids, and Solids02:26

Molecular Comparison of Gases, Liquids, and Solids

40.6K
Particles in a solid are tightly packed together (fixed shape) and often arranged in a regular pattern; in a liquid, they are close together with no regular arrangement (no fixed shape); in a gas, they are far apart with no regular arrangement (no fixed shape). Particles in a solid vibrate about fixed positions (cannot flow) and do not generally move in relation to one another; in a liquid, they move past each other (can flow) but remain in essentially constant contact; in a gas, they move...
40.6K
Asymmetric Lipid Bilayer01:35

Asymmetric Lipid Bilayer

7.2K
Biological membranes show uneven distribution of different types of lipids in the inner and outer layers, resulting in transverse asymmetric membranes. The treatment of the erythrocyte membrane with the enzyme phospholipase confirmed the asymmetric nature of the lipid bilayer. The enzyme hydrolyzes lipids into fatty acids and hydrophilic groups. The phospholipase acts only on the outer layer of the membrane, while the inner layer remains intact. The phospholipase treatment resulted in 80%...
7.2K

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Cooling Rate Dependent Ellipsometry Measurements to Determine the Dynamics of Thin Glassy Films
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通过信息失衡来选择玻璃动态的相关结构特征.

Anand Sharma1,2, Chen Liu3, Misaki Ozawa2

  • 1Indian Institute of Science Education and Research, Dr. Homi Bhabha Road, Pashan, Pune 411008, India.

The Journal of chemical physics
|November 12, 2024
PubMed
概括

研究人员使用信息失衡技术确定了影响玻璃形成液体缓慢动态的关键结构特征. 这种机器学习方法有助于在没有事先假设的情况下揭示复杂的玻璃行为背后的机制.

科学领域:

  • 凝聚物质物理学 凝聚物质物理学
  • 计算材料科学 计算材料科学

背景情况:

  • 动态异质性是形成玻璃的液体的标志,显著影响其性能.
  • 识别控制缓慢动态的结构特征对于理解玻璃过渡至关重要.

研究的目的:

  • 在模型玻璃成型液体中,以数值识别负责动态异质性的关键结构特征.
  • 应用非参数式机器学习技术用于特征选择和动态预测.

主要方法:

  • 利用信息失衡技术从物理动机描述器中进行特征选择.
  • 采用了监督 (动态和结构数据) 和无监督 (仅结构数据) 的学习方法.
  • 利用机器学习应用选定的功能来预测未来的动态.

主要成果:

  • 成功确定了有助于动态异质性的相关结构特征.
  • 以非参数的,模型不可知的方式证明了信息失衡技术的有效性.
  • 展示了选择的功能预测未来动态的能力.

结论:

  • 信息失衡技术是揭示复杂系统中的结构动态关系的强大工具.
  • 这种方法有助于识别控制玻璃材料缓慢动态的主导机制.

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Methods of Ex Situ and In Situ Investigations of Structural Transformations: The Case of Crystallization of Metallic Glasses
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Fluid-cell Raman Spectroscopy for operando Studies of Reaction and Transport Phenomena during Silicate Glass Corrosion
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Methods of Ex Situ and In Situ Investigations of Structural Transformations: The Case of Crystallization of Metallic Glasses
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  • 在材料设计和理解无序系统的基本性质方面存在潜在的应用.