Jove
Visualize
联系我们

相关概念视频

Lattice Centering and Coordination Number02:33

Lattice Centering and Coordination Number

9.9K
The structure of a crystalline solid, whether a metal or not, is best described by considering its simplest repeating unit, which is referred to as its unit cell. The unit cell consists of lattice points that represent the locations of atoms or ions. The entire structure then consists of this unit cell repeating in three dimensions. The three different types of unit cells present in the cubic lattice are illustrated in Figure 1.
Types of Unit Cells
Imagine taking a large number of identical...
9.9K
Trends in Lattice Energy: Ion Size and Charge02:54

Trends in Lattice Energy: Ion Size and Charge

24.2K
An ionic compound is stable because of the electrostatic attraction between its positive and negative ions. The lattice energy of a compound is a measure of the strength of this attraction. The lattice energy (ΔHlattice) of an ionic compound is defined as the energy required to separate one mole of the solid into its component gaseous ions. For the ionic solid sodium chloride, the lattice energy is the enthalpy change of the process:
24.2K
Bewley Lattice Diagram01:12

Bewley Lattice Diagram

840
The Bewley lattice diagram, developed by L. V. Bewley, effectively organizes the reflections occurring during transmission-line transients. It visually represents how voltage waves propagate and reflect within a transmission line, making it easier to understand the complex interactions that occur.
840
Dimensionless Groups in Fluid Mechanics01:15

Dimensionless Groups in Fluid Mechanics

425
Dimensionless groups in fluid mechanics provide simplified ratios that help analyze fluid behavior without relying on specific units. The Reynolds number (Re), which represents the ratio of inertial to viscous forces, distinguishes between laminar and turbulent flows, making it essential in the design of pipelines and aerodynamic surfaces. The Froude number (Fr), the ratio of inertial to gravitational forces, is particularly useful in predicting wave formation and hydraulic jumps in...
425
Region of Convergence of Laplace Tarnsform01:20

Region of Convergence of Laplace Tarnsform

697
The Region of Convergence (ROC) is a fundamental concept in signal processing and system analysis, particularly associated with the Laplace transform. The ROC represents an area in the complex plane where the Laplace transform of a given signal converges, determining the transform's applicability and utility.
Consider a decaying exponential signal that begins at a specific time. When deriving its Laplace transform, the time-domain variable is replaced with a complex variable. This...
697
Ziegler–Natta Chain-Growth Polymerization: Overview01:17

Ziegler–Natta Chain-Growth Polymerization: Overview

3.4K
Ziegler–Natta polymerization is another form of addition or chain‐growth polymerization used for synthesizing linear polymers over branched polymers. The catalyst used for polymerization is the Ziegler–Natta catalyst, named after Karl Ziegler and Giulio Natta, who developed it in 1953. This catalyst is an organometallic complex of titanium tetrachloride and triethyl aluminum, with the active form of the catalyst being an alkyl titanium compound. Using the Ziegler–Natta...
3.4K

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

Effective Delocalization in the One-Dimensional Anderson Model with Stealthy Disorder.

Physical review letters·2026
Same author

Trotter transition in Bardeen-Cooper-Schrieffer pairing dynamics.

Physical review. E·2026
Same author

Nonstabilizerness Dynamics in Many-Body Localized Systems.

Physical review letters·2026
Same author

Anticoncentration and Nonstabilizerness Spreading under Ergodic Quantum Dynamics.

Physical review letters·2025
Same author

Quantifying when hyperuniformity of a many-particle system leads to uniformity across length scales.

Physical review. E·2025
Same author

Scaling Theory of Fading Ergodicity.

Physical review letters·2025
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

相关实验视频

Updated: Sep 8, 2025

Fabrication and Characterization of Disordered Polymer Optical Fibers for Transverse Anderson Localization of Light
09:19

Fabrication and Characterization of Disordered Polymer Optical Fibers for Transverse Anderson Localization of Light

Published on: July 29, 2013

11.5K

对高维格的安德森定位的重规范化组

Boris L Altshuler1, Vladimir E Kravtsov2, Antonello Scardicchio2,3

  • 1Physics Department, Columbia University, New York, NY 10027.

Proceedings of the National Academy of Sciences of the United States of America
|August 26, 2025
PubMed
概括

本研究使用重新规范化组方法探索安德森模型的关键性质. 它揭示了碎形维度如何随着维度演变, 弥合了安德森转换的不同理论框架.

关键词:
安德森定位多体定位重新规范化组

更多相关视频

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
09:33

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

Published on: July 28, 2013

28.6K
Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
12:27

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Published on: February 15, 2017

7.0K

相关实验视频

Last Updated: Sep 8, 2025

Fabrication and Characterization of Disordered Polymer Optical Fibers for Transverse Anderson Localization of Light
09:19

Fabrication and Characterization of Disordered Polymer Optical Fibers for Transverse Anderson Localization of Light

Published on: July 29, 2013

11.5K
Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
09:33

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

Published on: July 28, 2013

28.6K
Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
12:27

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Published on: February 15, 2017

7.0K

科学领域:

  • 凝聚物质物理学
  • 统计力学
  • 量子系统

背景情况:

  • 安德森模型描述了无序系统中的电子定位.
  • 对于凝聚物质物理学来说,了解关键性质和转变至关重要.
  • 之前的工作为安德森转换引入了一个新的重规范化组 (RG) 框架.

研究的目的:

  • 调查安德森模型中关键性质的维度依赖性.
  • 分析贝塔函数的行为.
  • 调和不同的理论扩展和理解无关指数的作用.

主要方法:

  • 使用最近引入的重新规范化组 (RG) 框架.
  • 在各种维度限制中分析β函数的分数维度.
  • 使用随机正规图 (RRG) 结果的扩展.
  • 研究非线性西格玛模型中无关指数的出现.

主要成果:

  • 从d维度到RRG极限的分形维度β函数的顺演变.
  • 展示了如何调和d维和RRG扩展.
  • 通过无关指数控制的重新规范化组轨迹的维度依赖性.
  • 提出了一个关于碎形维度下限的猜测.

结论:

  • 开发的RG框架提供了一种统一的方法来研究跨不同维度的安德森过渡.
  • 这些发现为混乱的量子系统的行为提供了洞见.
  • 这项工作为未来的多体和不平衡量子系统研究奠定了基础.