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

Third Law of Thermodynamics02:38

Third Law of Thermodynamics

18.9K
A pure, perfectly crystalline solid possessing no kinetic energy (that is, at a temperature of absolute zero, 0 K) may be described by a single microstate, as its purity, perfect crystallinity,and complete lack of motion means there is but one possible location for each identical atom or molecule comprising the crystal (W = 1). According to the Boltzmann equation, the entropy of this system is zero.
18.9K
Dynamic Equilibrium02:20

Dynamic Equilibrium

51.6K
A reversible chemical reaction represents a chemical process that proceeds in both forward (left to right) and reverse (right to left) directions. When the rates of the forward and reverse reactions are equal, the concentrations of the reactant and product species remain constant over time and the system is at equilibrium. A special double arrow is used to emphasize the reversible nature of the reaction. The relative concentrations of reactants and products in equilibrium systems vary greatly;...
51.6K
Entropy and the Second Law of Thermodynamics01:20

Entropy and the Second Law of Thermodynamics

2.8K
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...
2.8K
Phase Transitions02:31

Phase Transitions

19.1K
Whether solid, liquid, or gas, a substance's state depends on the order and arrangement of its particles (atoms, molecules, or ions). Particles in the solid pack closely together, generally in a pattern. The particles vibrate about their fixed positions but do not move or squeeze past their neighbors. In liquids, although the particles are closely spaced, they are randomly arranged. The position of the particles are not fixed—that is, they are free to move past their neighbors to...
19.1K
States of Matter and Phase Changes00:59

States of Matter and Phase Changes

953
The internal energy of a substance—the total kinetic energy of all its molecules and the potential energy of their associated forces—depends on the strength of the intermolecular forces in the condensed phases and the pressure exerted on the substance. The internal energy of a substance is the highest in the gaseous state, the lowest in the solid state, and intermediate in the liquid state. Phase transitions are caused by changes in physical conditions, such as temperature and...
953
Phase Diagram01:19

Phase Diagram

5.9K
The phase of a given substance depends on the pressure and temperature. Thus, plots of pressure versus temperature showing the phase in each region provide considerable insights into the thermal properties of substances. Such plots are known as phase diagrams. For instance, in the phase diagram for water (Figure 1), the solid curve boundaries between the phases indicate phase transitions (i.e., temperatures and pressures at which the phases coexist).
5.9K

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

Setting benchmarks for practical quantum utility of combinatorial optimization.

Nature computational science·2026
Same author

General ab initio framework for electronic-order-induced lattice-dynamics symmetry breaking.

Science advances·2026
Same author

Prethermalization by random multipolar driving on a 78-qubit processor.

Nature·2026
Same author

Overcoming feature scarcity in complex system prediction: An alternative delay embedding.

Chaos (Woodbury, N.Y.)·2025
Same author

Multi-scaling reservoir computing learns noise-induced transitions with Lévy noise.

Chaos (Woodbury, N.Y.)·2025
Same author

Free-energy machine for combinatorial optimization.

Nature computational science·2025

相关实验视频

Updated: Jul 4, 2025

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

8.5K

学习不平衡的统计力学和动态相位过渡.

Ying Tang1,2, Jing Liu3,4, Jiang Zhang4,5

  • 1Institute of Fundamental and Frontier Sciences, University of Electronic Sciences and Technology of China, Chengdu, 611731, China. jamestang23@gmail.com.

Nature communications
|February 6, 2024
PubMed
概括

研究人员开发了一个机器学习框架来研究复杂的不平衡统计力学. 这种方法有效计算动态分区函数,使得在更高维度和超越稳定状态的相变的发现成为可能.

更多相关视频

Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package
06:37

Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package

Published on: September 17, 2021

4.5K
Combining Microfluidics and Microrheology to Determine Rheological Properties of Soft Matter during Repeated Phase Transitions
11:38

Combining Microfluidics and Microrheology to Determine Rheological Properties of Soft Matter during Repeated Phase Transitions

Published on: April 19, 2018

8.0K

相关实验视频

Last Updated: Jul 4, 2025

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

8.5K
Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package
06:37

Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package

Published on: September 17, 2021

4.5K
Combining Microfluidics and Microrheology to Determine Rheological Properties of Soft Matter during Repeated Phase Transitions
11:38

Combining Microfluidics and Microrheology to Determine Rheological Properties of Soft Matter during Repeated Phase Transitions

Published on: April 19, 2018

8.0K

科学领域:

  • 统计力学 统计力学
  • 机器学习 机器学习
  • 计算物理 计算物理

背景情况:

  • 没有平衡的统计力学描述了远离平衡的复杂系统.
  • 现有的方法与时间进化斗争,超越稳定状态,进入更高的维度.
  • 描述动态相位转换需要跟踪系统在控制参数下的演变.

研究的目的:

  • 开发一个一般的计算框架来研究不平衡系统的时间演变.
  • 为了实现动态分区函数的有效计算,以发现相位过渡.
  • 将动态相变的研究扩展到更高的维度和任意时间.

主要方法:

  • 杆式变量自回归网络用于高效的计算.
  • 开发了一个通用计算框架,用于时间进化研究.
  • 将框架应用于最多三维的结构玻璃的动力约束模型.

主要成果:

  • 成功发现了旋转翻转的活跃-无活跃相位过渡.
  • 确定了研究模型的动态相位图.
  • 确定了新的扩展关系,证明了框架的能力.

结论:

  • 开发的机器学习框架为研究不平衡系统提供了一种有效的方法.
  • 该方法可以发现复杂系统和更高维度中的动态相变.
  • 强调机器学习在推进非平衡统计力学研究方面的巨大潜力.