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Membrane Fluidity01:23

Membrane Fluidity

156.9K
Cell membranes are composed of phospholipids, proteins, and carbohydrates loosely attached to one another through chemical interactions. Molecules are generally able to move about in the plane of the membrane, giving the membrane its flexible nature called fluidity. Two other features of the membrane contribute to membrane fluidity: the chemical structure of the phospholipids and the presence of cholesterol in the membrane.
156.9K
The Fluid Mosaic Model01:34

The Fluid Mosaic Model

153.9K
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.
153.9K
Accelerating Fluids01:17

Accelerating Fluids

1.5K
When a fluid is in constant acceleration, the pressure and buoyant force equations are modified. Suppose a beaker is placed in an elevator accelerating upward with a constant acceleration, a. In the beaker, assume there is a thin cylinder of height h with an infinitesimal cross-sectional area, ΔS.
The motion of the liquid within this infinitesimal cylinder is considered to obtain the pressure difference. Three vertical forces act on this liquid:
1.5K
Fluid Mosaic Model01:19

Fluid Mosaic Model

13.0K
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...
13.0K
Viscosity of Fluid01:19

Viscosity of Fluid

719
Viscosity measures the resistance a fluid offers to flow and deformation. It results from internal friction between layers of fluid moving relative to one another. Dynamic viscosity, denoted by the Greek letter mu (μ), quantifies the force needed to move one fluid layer over another. For Newtonian fluids like water and air, the relationship between the shearing stress and the rate of shearing strain is linear, meaning their viscosity remains constant regardless of the applied stress.
719
Phase Transitions: Vaporization and Condensation02:39

Phase Transitions: Vaporization and Condensation

18.7K
The physical form of a substance changes on changing its temperature. For example, raising the temperature of a liquid causes the liquid to vaporize (convert into vapor). The process is called vaporization—a surface phenomenon. Vaporization occurs when the thermal motion of the molecules overcome the intermolecular forces, and the molecules (at the surface) escape into the gaseous state. When a liquid vaporizes in a closed container, gas molecules cannot escape. As these gas phase...
18.7K

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相关实验视频

Updated: Sep 16, 2025

Confocal Imaging of Confined Quiescent and Flowing Colloid-polymer Mixtures
10:56

Confocal Imaging of Confined Quiescent and Flowing Colloid-polymer Mixtures

Published on: May 20, 2014

12.2K

在修改的零散粒子模型中增强了冷凝液流动性.

Alena Taskina1,2, Devika Magan1,3, Simon Dannenberg1

  • 1University of Göttingen, Institute for the Dynamics of Complex Systems, Friedrich-Hund-Platz 1, 37077 Göttingen, Germany.

The Journal of chemical physics
|July 8, 2025
PubMed
概括
此摘要是机器生成的。

经过修改的零散粒子模型加速了生物分子凝聚物的模拟. 这些模型捕捉了基本的流体和结构性质,使得以前被缓慢的动力学所限制的复杂系统的研究成为可能.

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Microfluidic Devices for Characterizing Pore-scale Event Processes in Porous Media for Oil Recovery Applications
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Microfluidic Devices for Characterizing Pore-scale Event Processes in Porous Media for Oil Recovery Applications

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High Throughput Single-cell and Multiple-cell Micro-encapsulation
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High Throughput Single-cell and Multiple-cell Micro-encapsulation

Published on: June 15, 2012

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相关实验视频

Last Updated: Sep 16, 2025

Confocal Imaging of Confined Quiescent and Flowing Colloid-polymer Mixtures
10:56

Confocal Imaging of Confined Quiescent and Flowing Colloid-polymer Mixtures

Published on: May 20, 2014

12.2K
Microfluidic Devices for Characterizing Pore-scale Event Processes in Porous Media for Oil Recovery Applications
08:38

Microfluidic Devices for Characterizing Pore-scale Event Processes in Porous Media for Oil Recovery Applications

Published on: January 16, 2018

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High Throughput Single-cell and Multiple-cell Micro-encapsulation
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High Throughput Single-cell and Multiple-cell Micro-encapsulation

Published on: June 15, 2012

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科学领域:

  • 生物物理学的生物物理.
  • 计算生物学 计算生物学
  • 软物质物理学 软物质物理学

背景情况:

  • 生物分子凝聚物通过蛋白质和核酸的液体液相分离 (LLPS) 形成.
  • 粗粒模型,特别是不齐的粒子模型,对于模拟凝结物行为至关重要.
  • 经典的斑点粒子模型往往表现出缓慢的动态,阻碍了对流体凝聚物的研究.

研究的目的:

  • 开发和评估修改的零散粒子模型,用于加速模拟生物分子凝聚物.
  • 调查增强模拟速度的变体,同时保持平衡性质.
  • 为了研究更大,更复杂的凝结体系统.

主要方法:

  • 模拟修改的斑块粒子模型,具有灵活的斑块和弱同otropic核心吸引力的模拟.
  • 动力学,相态度和局部结构的比较,与经典的零散粒子模型进行比较.
  • 分析系统放松时间和形成流体凝结物的能力.

主要成果:

  • 修改后的模型显著加快了系统动态,与经典的不整的粒子模型相比.
  • 保持了关键的平衡特征,包括相位行为和局部结构.
  • 增强的动态允许模拟更大的系统,降低计算成本.

结论:

  • 修改的零散粒子模型为模拟生物分子凝聚物提供了一种多功能和高效的工具.
  • 这些模型克服了经典方法中缓慢动态的局限性.
  • 它们有助于更深入地了解液体生物分子凝聚物的形成和动态.