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相关概念视频

Entropy Change in Reversible Processes01:10

Entropy Change in Reversible Processes

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In the Carnot engine, which achieves the maximum efficiency between two reservoirs of fixed temperatures, the total change in entropy is zero. The observation can be generalized by considering any reversible cyclic process consisting of many Carnot cycles. Thus, it can be stated that the total entropy change of any ideal reversible cycle is zero.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.
2.6K
Entropy and the Second Law of Thermodynamics01:20

Entropy and the Second Law of Thermodynamics

2.9K
The second law of thermodynamics can be stated quantitatively using the concept of entropy. Entropy is the measure of disorder of the system.
The relation  between entropy and disorder can be illustrated with the example of the phase change of ice to water. In ice, the molecules are located at specific sites giving a solid state, whereas, in a liquid form, these molecules are much freer to move. The molecular arrangement has therefore become more randomized. Although the change in average...
2.9K
First Law: Particles in One-dimensional Equilibrium01:10

First Law: Particles in One-dimensional Equilibrium

7.0K
Newton's first law of motion states that a body at rest remains at rest, or if in motion, remains in motion at constant velocity, unless acted on by a net external force. It also states that there must be a cause for any change in velocity (a change in either magnitude or direction) to occur. This cause is a net external force. For example, consider what happens to an object sliding along a rough horizontal surface. The object quickly grinds to a halt, due to the net force of friction. If...
7.0K
Theories of Dissolution: The Danckwerts' Model and Interfacial Barrier Model01:09

Theories of Dissolution: The Danckwerts' Model and Interfacial Barrier Model

343
Various dissolution theories provide insight into the factors that influence the dissolution rate. Danckwerts' Model suggests that turbulence, rather than a stagnant layer, characterizes the dissolution medium at the solid-liquid interface. In this model, the agitated solvent contains macroscopic packets that move to the interface via eddy currents, facilitating the absorption and delivery of the drug to the bulk solution. The regular replenishment of solvent packets maintains the...
343
Intrinsically Disordered Proteins02:18

Intrinsically Disordered Proteins

17.9K
Intrinsically disordered proteins are a group of proteins that do not fold into specific three-dimensional structures. Their structural flexibility allows them to complement ordered proteins to perform functions that are inaccessible to rigid structures. They are more common in eukaryotes than prokaryotes and may either be exclusively intrinsically disordered or hybrid proteins, consisting of a mix of ordered and disordered regions. The absence of a rigid structure in these proteins can be...
17.9K
The Second Law of Thermodynamics01:14

The Second Law of Thermodynamics

5.4K
In the quest to identify a property that may reliably predict the spontaneity of a process, a promising candidate has been identified: entropy. Scientists refer to the measure of randomness or disorder within a system as entropy. High entropy means high disorder and low energy. To better understand entropy, think of a student’s bedroom. If no energy or work were put into it, the room would quickly become messy. It would exist in a very disordered state, one of high entropy. Energy must be...
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相关实验视频

Updated: Jul 19, 2025

Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time
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Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time

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在多体互连系统中出现的信息动态.

Wout Merbis1, Manlio de Domenico2

  • 1Dutch Institute for Emergent Phenomena (DIEP), Institute for Theoretical Physics (ITFA), University of Amsterdam, 1090 GL Amsterdam, The Netherlands.

Physical review. E
|August 16, 2023
PubMed
概括

本研究引入了一个新的数学框架,用于对复杂网络的信息流进行建模. 它使用量子启发的方法揭示了隐藏的网络动态,适用于各种系统,如流行病和社会传染.

科学领域:

  • 复杂系统科学 复杂系统科学
  • 统计力学 统计力学
  • 信息理论 信息理论

背景情况:

  • 物理系统中的信息是使用统计力学和信息理论来分析的.
  • 这种方法已经应用于复杂的网络,如蛋白质相互作用和大脑模型,灵感来自量子统计物理学.

研究的目的:

  • 提出一个一般的数学框架,用于模拟复杂网络上的信息动态.
  • 为了使节点能够使用向量值状态携带多种类型的信息.
  • 将焦点从节点-节点交互转移到网络配置之间的信息流.

主要方法:

  • 在复杂网络上开发信息动态的一般数学框架.
  • 使用矢量值的节点状态来表示多种信息类型.
  • 分析网络配置之间的信息流,灵感来自量子多体系统.

主要成果:

  • 发现了网络旋转模型 (例如,选民,动力动态) 中的基本差异,这些差异无法通过经典分析检测到.
  • 证明了该框架对在低维网络上传播的流行病的适用性.
  • 提供了一种方法,使量子多体系统的分析技术适应网络动态.

结论:

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  • 拟议的框架为理解复杂系统中的信息动态提供了一种新的方法.
  • 它可以比传统方法更深入地分析网络结构和动态.
  • 这项工作将统计力学,信息理论和网络科学结合起来,用于更广泛的应用.