Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Entropy and the Second Law of Thermodynamics01:20

Entropy and the Second Law of Thermodynamics

5.1K
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...
5.1K
Entropy and the Second Law of Thermodynamics01:26

Entropy and the Second Law of Thermodynamics

20
Consider an isolated system in which a hot object is placed in contact with a cold one. This is an irreversible process that eventually leads both objects to reach the same equilibrium temperature. It is crucial to note that the constituents of any substance exhibit increased disorder at higher temperatures. As a cold substance absorbs heat, its constituents become more disordered. The energy transfer from a hotter object to a cooler one increases the system's disorder or randomness. This...
20
Entropy Change in Reversible Processes01:10

Entropy Change in Reversible Processes

3.3K
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.
3.3K
Entropy02:39

Entropy

36.9K
Salt particles that have dissolved in water never spontaneously come back together in solution to reform solid particles. Moreover, a gas that has expanded in a vacuum remains dispersed and never spontaneously reassembles. The unidirectional nature of these phenomena is the result of a thermodynamic state function called entropy (S). Entropy is the measure of the extent to which the energy is dispersed throughout a system, or in other words, it is proportional to the degree of disorder of a...
36.9K
Entropy01:18

Entropy

3.7K
The first law of thermodynamics is quantitatively formulated via an equation relating the internal energy of a system, the heat exchanged by it, and the work done on it. A quantitative formulation of the second law of thermodynamics leads to defining a state function, the entropy.
When an ideal gas expands isothermally, the disorder in the gas increases. From the molecular perspective, the gas molecules have more volume to move around in.
Consider an infinitesimal step in the expansion, which...
3.7K
Entropy Changes Accompanying Specific Processes01:21

Entropy Changes Accompanying Specific Processes

18
Entropy, a measure of disorder in a system, changes during phase transitions like freezing or boiling. At the transition temperature Ttrs, where two phases are in equilibrium, the phase transition is a reversible process. The entropy change can be calculated from a substance's enthalpy of transition using the equation ΔStrs = ΔtrsH /Ttrs.When a perfect gas expands isothermally from one volume to another, entropy increases logarithmically with volume. Conversely, isothermal compression...
18

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Neo-Gibbsian statistical energetics with applications to nonequilibrium cells.

Biophysical journal·2026
Same author

The application value of peripheral plasmablasts in the assessment of disease activity and treatment response in systemic lupus erythematosus.

Clinical and experimental rheumatology·2025
Same author

The DND1-NANOS3 complex shapes the primordial germ cell transcriptome via a heptanucleotide sequence in mRNA 3' UTRs.

bioRxiv : the preprint server for biology·2025
Same author

Construction and evaluation of an emotion-inducing video dataset towards Chinese elderly healthy controls and individuals with mild cognitive impairment.

Cognitive neurodynamics·2025
Same author

A progressive attention-based cross-modal fusion network for cardiovascular disease detection using synchronized electrocardiogram and phonocardiogram signals.

PeerJ. Computer science·2025
Same author

Solving Lyapunov equations for electrically driven ternary electrolytes: Application to long-range van der Waals interactions.

Physical review. E·2025

相关实验视频

Updated: Mar 3, 2026

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids
11:03

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids

Published on: December 4, 2017

9.1K

非高斯活性物质的 entropy 生产:一个统一的波动定理和深度学习框架.

Yuanfei Huang1,2, Chengyu Liu3, Bing Miao4

  • 1Asia Pacific Center for Theoretical Physics, Pohang-si, Gyeongsangbuk-do, 37673, Republic of Korea.

Physical review letters
|March 1, 2026
PubMed
概括

我们开发了一个框架来计算非高斯波动的活性物质系统中的产量. 这种方法提供了一种统一的方法和计算工具,用于研究复杂的不平衡行为.

更多相关视频

Controlling Flow Speeds of Microtubule-Based 3D Active Fluids Using Temperature
08:04

Controlling Flow Speeds of Microtubule-Based 3D Active Fluids Using Temperature

Published on: November 26, 2019

7.6K
Cooling an Optically Trapped Ultracold Fermi Gas by Periodical Driving
11:21

Cooling an Optically Trapped Ultracold Fermi Gas by Periodical Driving

Published on: March 30, 2017

7.9K

相关实验视频

Last Updated: Mar 3, 2026

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids
11:03

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids

Published on: December 4, 2017

9.1K
Controlling Flow Speeds of Microtubule-Based 3D Active Fluids Using Temperature
08:04

Controlling Flow Speeds of Microtubule-Based 3D Active Fluids Using Temperature

Published on: November 26, 2019

7.6K
Cooling an Optically Trapped Ultracold Fermi Gas by Periodical Driving
11:21

Cooling an Optically Trapped Ultracold Fermi Gas by Periodical Driving

Published on: March 30, 2017

7.9K

科学领域:

  • 物理 物理学 物理
  • 统计力学 统计力学
  • 柔软的物质 软的物质

背景情况:

  • 活性物质系统表现出由内部能量消耗驱动的复杂的不平衡动态.
  • 了解生成对于描述这些系统至关重要,但非高斯波动带来了挑战.
  • 随机热力学现有的方法经常与非高斯活跃波动作斗争.

研究的目的:

  • 开发一个一般的理论框架来推导由非高斯活跃波动驱动的活性物质系统中的生产率.
  • 为这些系统建立波动定理和热力学不等式.
  • 引入一种基于深度学习的新计算方法,以有效计算产量.

主要方法:

  • 利用概率流等效技术来推导出产生的分解公式.
  • 证明了详细和完整的波动定理,包括热力学第二定律.
  • 提出了一种深度学习方法,将莱维分数纳入高效的生成计算.

主要成果:

  • 推导出适用于非高斯活跃系统的严格生成分解公式.
  • 确定总产量满足了详细和完整的波动定理.
  • 展示了活性物质系统的热力学第二定律.
  • 在活性浴和活性聚合物模型中的布朗粒子上验证了深度学习方法.

结论:

  • 提出的框架提供了一种统一的方法来分析活性物质中的产量.
  • 开发的计算工具可以有效地调查复杂的不平衡现象.
  • 这些发现将随机热力学扩展到具有非高斯活跃波动的系统.