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相关概念视频

Fluid Mosaic Model01:34

Fluid Mosaic Model

The fluid mosaic model was first proposed as a visual representation of research observations. The model comprises the composition and dynamics of membranes and serves as a foundation for future membrane-related studies. The model depicts the structure of the plasma membrane with a variety of components, which include phospholipids, proteins, and carbohydrates. These integral molecules are loosely bound, defining the cell’s border and providing fluidity for optimal function.LipidsThe most...
Molecular Models02:00

Molecular Models

Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.
Fluid Mosaic Model01:19

Fluid Mosaic Model

Scientists identified the plasma membrane in the 1890s and its principal chemical components (lipids and proteins) by 1915. The model for plasma membrane structure, proposed in 1935 by Hugh Davson and James Danielli, was the first model to be widely accepted in the scientific community. The model was based on the plasma membrane's "railroad track" appearance in early electron micrographs. Davson and Danielli theorized that the plasma membrane's structure resembled a sandwich with the analogy of...
Two Components: Liquid–Liquid Systems01:27

Two Components: Liquid–Liquid Systems

A pressure-composition phase diagram explicitly describes the behavior of an ideal solution of two volatile liquids under varying pressures and compositions. A pressure-composition diagram has two main curves. The bubble point curve represents the plot of pressure versus liquid mole fraction. It indicates the pressure at which the first bubble of vapor forms from the liquid phase as the system pressure decreases.The dew point curve is the pressure versus vapor mole fraction. It indicates the...

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Updated: Jun 29, 2026

Preparation of Monodomain Liquid Crystal Elastomers and Liquid Crystal Elastomer Nanocomposites
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基于神经网络的液晶张量模型,具有分子级信息的液晶.

Baoming Shi1, Apala Majumdar2, Lei Zhang3

  • 1Peking University, School of Mathematical Sciences, Beijing 100871, China.

Physical review. E
|February 20, 2026
PubMed
概括

与传统模型相比,用于液晶 (LC) 的新神经网络张量 (NN-tensor) 模型提供了更高的准确性和相位过渡预测. 这种高效的框架准确地计算了多个阶段的复杂LC微结构.

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相关实验视频

Last Updated: Jun 29, 2026

Preparation of Monodomain Liquid Crystal Elastomers and Liquid Crystal Elastomer Nanocomposites
12:21

Preparation of Monodomain Liquid Crystal Elastomers and Liquid Crystal Elastomer Nanocomposites

Published on: February 6, 2016

Preparation of Liquid Crystal Networks for Macroscopic Oscillatory Motion Induced by Light
07:56

Preparation of Liquid Crystal Networks for Macroscopic Oscillatory Motion Induced by Light

Published on: September 20, 2017

Novel Techniques for Observing Structural Dynamics of Photoresponsive Liquid Crystals
10:35

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科学领域:

  • 材料科学 材料科学 材料科学
  • 计算物理 计算物理
  • 软物质物理学 软物质物理学

背景情况:

  • 兰道-德热内斯 (LdG) 模型是液晶 (LC) 阶段的连续理论.
  • 与分子级模拟相比,LdG模型的准确性和物理信息较低.
  • 精确的LC相建模对于材料科学和设备应用至关重要.

研究的目的:

  • 为液晶开发一种基于神经网络的新型张量 (NN-tensor) 模型.
  • 为了提高LC相模拟的精度和物理准确性.
  • 为了高效计算稳定的LC配置,并解决复杂的微观结构.

主要方法:

  • 开发了一个由底层分子模型监督的NN-tensor模型.
  • 将NN-tensor模型集成到第二个神经网络中,以实现高效的计算.
  • 验证了 nematic 和 smectic 液晶相的模型.

主要成果:

  • 该NN-tensor模型实现了与分子模型可比的能量精度.
  • 它准确地捕获了同otropic-nematic 阶段过渡,超过了 LdG 模型.
  • 该模型量化预测了涂层厚度,并解决了Omega和T形粒边界等复杂的微观结构.

结论:

  • 该NN-tensor框架为计算LC配置提供了一个统一,高效和物理忠实的方法.
  • 这种方法克服了传统方法在解决复杂的LC微结构方面的局限性.
  • 这种NN-tensor模型在模拟各种液晶相方面取得了重大进展.