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

Correlation of Experimental Data01:23

Correlation of Experimental Data

217
Dimensional analysis simplifies complex physical problems and guides experimental investigations, but it does not provide complete solutions. It identifies the dimensionless groups that influence a phenomenon, but experimental data is needed to establish the specific relationships and validate theoretical predictions.
For example, a spherical particle moving through a viscous fluid experiences drag. Dimensional analysis shows that the drag force depends on the particle's diameter, velocity,...
217
Dimensional Analysis01:27

Dimensional Analysis

303
Dimensional analysis is a valuable technique in fluid mechanics for simplifying complex problems by reducing them into dimensionless groups. These groups capture the essential relationships between the variables involved, allowing researchers and engineers to analyze fluid flow without dealing with each variable individually. This approach reduces the number of independent variables, allowing for easier analysis and better understanding of physical phenomena.
In fluid mechanics, dimensional...
303
Problem Solving: Dimensional Analysis01:08

Problem Solving: Dimensional Analysis

3.3K
Every mathematical equation that connects separate distinct physical quantities must be dimensionally consistent, which implies it must abide by two rules. For this reason, the concept of dimension is crucial. The first rule is that an equation's expressions on either side of an equality must have the exact same dimension, i.e., quantities of the same dimension can be added or removed. The second rule stipulates that all popular mathematical functions, such as exponential, logarithmic, and...
3.3K
The Integrated Rate Law: The Dependence of Concentration on Time02:39

The Integrated Rate Law: The Dependence of Concentration on Time

34.6K
While the differential rate law relates the rate and concentrations of reactants, a second form of rate law called the integrated rate law relates concentrations of reactants and time. Integrated rate laws can be used to determine the amount of reactant or product present after a period of time or to estimate the time required for a reaction to proceed to a certain extent. For example, an integrated rate law helps determine the length of time a radioactive material must be stored for its...
34.6K
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

29
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
29
Behavior of Gas Molecules: Molecular Diffusion, Mean Free Path, and Effusion03:48

Behavior of Gas Molecules: Molecular Diffusion, Mean Free Path, and Effusion

28.6K
Although gaseous molecules travel at tremendous speeds (hundreds of meters per second), they collide with other gaseous molecules and travel in many different directions before reaching the desired target. At room temperature, a gaseous molecule will experience billions of collisions per second. The mean free path is the average distance a molecule travels between collisions. The mean free path increases with decreasing pressure; in general, the mean free path for a gaseous molecule will be...
28.6K

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

Recent Biomedical Applications of Carbon Quantum Dots in Cancer Treatment.

The journal of physical chemistry. C, Nanomaterials and interfaces·2025
Same author

Beyond Solution Chemistry: Mechanochemistry Enables Clustered Defects in Metal-Organic Frameworks.

Inorganic chemistry·2025
Same author

Application and significance of SIRVB model in analyzing COVID-19 dynamics.

Scientific reports·2025
Same author

Application and Significance of SIRVB Model in Analyzing COVID-19 Dynamics.

medRxiv : the preprint server for health sciences·2024
Same author

Structured Stochastic Curve Fitting without Gradient Calculation.

Journal of Computational Mathematics and Data Science·2024
Same author

Physical Chemistry Lab for Data Analysis of COVID-19 Spreading Kinetics in Different Countries.

Journal of chemical education·2024

相关实验视频

Updated: Jun 7, 2025

Synthesis of Cyclic Polymers and Characterization of Their Diffusive Motion in the Melt State at the Single Molecule Level
06:55

Synthesis of Cyclic Polymers and Characterization of Their Diffusive Motion in the Melt State at the Single Molecule Level

Published on: September 26, 2016

7.8K

扩散关联率方程的维度分析.

Jixin Chen1

  • 1Department of Chemistry and Biochemistry, Nanoscale and Quantum Phenomena Institute, Ohio University, Athens, Ohio 45701, USA.

AIP advances
|November 18, 2024
PubMed
概括
此摘要是机器生成的。

预测反应速率是很困难的,因为过时的Fick.

更多相关视频

Measurement of Particle Size Distribution in Turbid Solutions by Dynamic Light Scattering Microscopy
09:16

Measurement of Particle Size Distribution in Turbid Solutions by Dynamic Light Scattering Microscopy

Published on: January 9, 2017

14.3K
Image Processing Protocol for the Analysis of the Diffusion and Cluster Size of Membrane Receptors by Fluorescence Microscopy
12:15

Image Processing Protocol for the Analysis of the Diffusion and Cluster Size of Membrane Receptors by Fluorescence Microscopy

Published on: April 9, 2019

8.7K

相关实验视频

Last Updated: Jun 7, 2025

Synthesis of Cyclic Polymers and Characterization of Their Diffusive Motion in the Melt State at the Single Molecule Level
06:55

Synthesis of Cyclic Polymers and Characterization of Their Diffusive Motion in the Melt State at the Single Molecule Level

Published on: September 26, 2016

7.8K
Measurement of Particle Size Distribution in Turbid Solutions by Dynamic Light Scattering Microscopy
09:16

Measurement of Particle Size Distribution in Turbid Solutions by Dynamic Light Scattering Microscopy

Published on: January 9, 2017

14.3K
Image Processing Protocol for the Analysis of the Diffusion and Cluster Size of Membrane Receptors by Fluorescence Microscopy
12:15

Image Processing Protocol for the Analysis of the Diffusion and Cluster Size of Membrane Receptors by Fluorescence Microscopy

Published on: April 9, 2019

8.7K

科学领域:

  • 物理化学 物理化学
  • 化学动力学 化学动力学
  • 统计力学 统计力学

背景情况:

  • 扩散吸附/结合对于许多化学和物理过程至关重要.
  • 现有的基于百年历史的方程的预测模型与实验数据存在显著差异.
  • 这些差异阻碍了各种领域的准确率预测,如催化,生物分子相互作用和环境动态.

研究的目的:

  • 解决目前用于预测扩散吸附/结合率的模型的局限性.
  • 调查反应动力学中Fick梯度的理想化假设所产生的不准确性.
  • 提出一种用于准确建模扩散控制反应的新方法.

主要方法:

  • 在三维系统中分析Fick梯度的时间依赖演化曲线.
  • 开发基于单分子扩散概率密度函数的溶液.
  • 扩散过程的离散建模.

主要成果:

  • 确定Fick梯度中斜率的高估是错误的主要来源.
  • 对扩散动态更准确地表示的演示.
  • 通过离散建模验证拟议的方法.

结论:

  • 理想化的菲克梯度模型在许多场景中显著高估了反应速率.
  • 使用单分子扩散概率密度函数的新方法可以更准确地预测反应动力学.
  • 这项工作为扩散有限过程中改进的理论模型提供了基础.