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

Molecular Models02:00

Molecular Models

37.7K
Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.
37.7K
Motion Of A Charged Particle In A Magnetic Field01:22

Motion Of A Charged Particle In A Magnetic Field

4.4K
A charged particle experiences a force when moving through a magnetic field. Consider the field to be uniform and the charged particle to move perpendicular to it. If the field is in a vacuum, the magnetic field is the dominant factor determining the motion. Since the magnetic force is perpendicular to the direction of motion, a charged particle follows a curved path. The particle continues to follow this curved path until it forms a complete circle. Another way to look at this is that the...
4.4K
Potential Due to a Polarized Object01:29

Potential Due to a Polarized Object

353
A neutral atom consists of a positively charged nucleus surrounded by a negatively charged electron cloud. When placed in an external electric field, the external electric force pulls the electrons and nucleus apart, opposite to the intrinsic attraction between the nucleus and the electrons. The opposing forces balance each other with a slight shift between the center of masses of the nucleus and the electron cloud, resulting in a polarized atom. On the other hand, a few molecules, like water,...
353
Molecular Geometry and Dipole Moments02:36

Molecular Geometry and Dipole Moments

12.4K
The VSEPR theory can be used to determine the electron pair geometries and molecular structures as follows:
12.4K
MO Theory and Covalent Bonding02:40

MO Theory and Covalent Bonding

10.2K
The molecular orbital theory describes the distribution of electrons in molecules in a manner similar to the distribution of electrons in atomic orbitals. The region of space in which a valence electron in a molecule is likely to be found is called a molecular orbital. Mathematically, the linear combination of atomic orbitals (LCAO) generates molecular orbitals. Combinations of in-phase atomic orbital wave functions result in regions with a high probability of electron density, while...
10.2K
Thermodynamic Potentials01:26

Thermodynamic Potentials

749
Thermodynamic potentials are state functions that are extremely useful in analyzing a thermodynamic system. They have dimensions of energy. The four important thermodynamic potentials are internal energy, enthalpy, Helmholtz free energy, and Gibbs free energy. These thermodynamic potentials can be expressed using two of the following variables: pressure, volume, temperature, and entropy. These two variables are expressed as the rate of change of the thermodynamic potential with respect to other...
749

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 authorSame journal

Reactive Chemistry at the Unrestricted Coupled Cluster Level: High-Throughput Calculations for Training Machine Learning Potentials.

Journal of chemical theory and computation·2026
Same author

Vibrational and Electronic Spectroscopies of Dibenzoterrylene Conformers: Computational Insights.

The journal of physical chemistry letters·2026
Same author

Learning molecular determinants of selective small-molecule partitioning across biomolecular condensates.

bioRxiv : the preprint server for biology·2026
Same author

Tacticity-Regulated Electrochemical Properties of Poly(2,2,6,6-tetramethylpiperidinyloxy Methacrylate).

Journal of the American Chemical Society·2026
Same author

Enhancing Molecular Dipole Moment Prediction with Multitask Machine Learning.

The journal of physical chemistry letters·2026
Same author

Knowledge distillation of noisy force labels for improved coarse-grained force fields.

The Journal of chemical physics·2026

相关实验视频

Updated: May 22, 2025

Vibrational Spectra of a N719-Chromophore/Titania Interface from Empirical-Potential Molecular-Dynamics Simulation, Solvated by a Room Temperature Ionic Liquid
08:54

Vibrational Spectra of a N719-Chromophore/Titania Interface from Empirical-Potential Molecular-Dynamics Simulation, Solvated by a Room Temperature Ionic Liquid

Published on: January 25, 2020

5.6K

影子分子动力学与机器学习的灵活电荷潜力

Cheng-Han Li1, Mehmet Cagri Kaymak1, Maksim Kulichenko1

  • 1Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States.

Journal of chemical theory and computation
|March 14, 2025
PubMed
概括

我们使用机器学习开发了一种新的分子动力学方法,以准确模拟分子行为. 这种方法提高了模拟稳定性,并降低了用于预测诸如红外光谱等分子性质的计算成本.

更多相关视频

Author Spotlight: Advancing Cell Membrane Biophysics - Exploring Interactions and Challenges Through Experimental and Computational Approaches
07:31

Author Spotlight: Advancing Cell Membrane Biophysics - Exploring Interactions and Challenges Through Experimental and Computational Approaches

Published on: September 1, 2023

2.1K
Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion
09:17

Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion

Published on: March 1, 2022

3.0K

相关实验视频

Last Updated: May 22, 2025

Vibrational Spectra of a N719-Chromophore/Titania Interface from Empirical-Potential Molecular-Dynamics Simulation, Solvated by a Room Temperature Ionic Liquid
08:54

Vibrational Spectra of a N719-Chromophore/Titania Interface from Empirical-Potential Molecular-Dynamics Simulation, Solvated by a Room Temperature Ionic Liquid

Published on: January 25, 2020

5.6K
Author Spotlight: Advancing Cell Membrane Biophysics - Exploring Interactions and Challenges Through Experimental and Computational Approaches
07:31

Author Spotlight: Advancing Cell Membrane Biophysics - Exploring Interactions and Challenges Through Experimental and Computational Approaches

Published on: September 1, 2023

2.1K
Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion
09:17

Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion

Published on: March 1, 2022

3.0K

科学领域:

  • 计算化学是一种计算化学.
  • 材料科学是一种材料科学.
  • 分子动力学模拟的模拟.

背景情况:

  • 精确的分子动力学 (MD) 模拟需要精确的原子间电位.
  • 电荷平衡 (QE) 模型估计原子电荷,但可能是计算密集的.
  • 机器学习 (ML) 为开发更高效,更准确的模型提供了强大的工具.

研究的目的:

  • 引入一个扩展的拉格朗日影分子动力学 (EL-SMD) 方案.
  • 将第二级电荷平衡 (SOCE) 模型与ML衍生的原子间电位的参数集成.
  • 为了提高分子动力学模拟的准确性,稳定性和效率.

主要方法:

  • 开发了一个EL-SMD方案,使用来自放松原子电荷的波恩-奥本海默电位.
  • 利用神经网络对SOCE模型进行参数化,以环境依赖的电子阴性和化学硬度.
  • 评估了固定与环境依赖的QE参数对模拟准确性的影响.
  • 使用双极自相关函数计算分子红外光谱.

主要成果:

  • 在EL-SMD方案中,数值稳定性得到改善,库伦电位计算减少.
  • 实现了高效准确的分子动力学模拟,具有优异的长期轨迹稳定性.
  • 基于ML的QE参数化显著提高了灵活电荷潜力的准确性.
  • 计算的红外光谱与实验数据准确匹配,验证了EL-SMD方法.

结论:

  • 拟议的EL-SMD方案具有ML参数化的灵活电荷潜力,为分子模拟提供了强大而准确的方法.
  • 通过ML获得的环境依赖的原子参数对于捕捉精确的分子行为至关重要.
  • 这种方法为计算化学和材料科学研究提供了重大进展.