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

Formal Charges02:42

Formal Charges

32.6K
In some cases, there are seemingly more than one valid Lewis structures for molecules and polyatomic ions. The concept of formal charges can be used to help predict the most appropriate Lewis structure when more than one reasonable structure exists.
32.6K
Sources and Properties of Electric Charge01:15

Sources and Properties of Electric Charge

10.1K
All objects we see around us consist of atoms, which combine to form molecules. The lightest element in the universe is hydrogen, and a hydrogen atom consists of a positively charged proton and a negatively charged electron. The magnitude of charge that a proton and an electron carry are the same, and it is the fundamental unit of charge. In SI units, it is 1.602 times 10-19 coulomb.
Most atoms additionally constitute another fundamental particle, the neutron. It carries no electrical charge. A...
10.1K
Atomic Radii and Effective Nuclear Charge03:08

Atomic Radii and Effective Nuclear Charge

51.6K
The elements in groups of the periodic table exhibit similar chemical behavior. This similarity occurs because the members of a group have the same number and distribution of electrons in their valence shells.
51.6K
Coulomb's Law01:30

Coulomb's Law

9.2K
Experiments with electric charges have shown that if two objects each have an electric charge, they exert an electric force on each other. The magnitude of the force is linearly proportional to the net charge on each object and inversely proportional to the square of the distance between them. The direction of the force vector is along the imaginary line joining the two objects and is dictated by the signs of the charges involved.
Newton's third law applies to the Coulomb force — the...
9.2K
Lewis Structures and Formal Charges02:19

Lewis Structures and Formal Charges

14.3K
Lewis symbols can be used to indicate the formation of covalent bonds, which are shown in Lewis structures—drawings that describe the bonding in molecules and polyatomic ions. The periodic table can be used to predict the number of valence electrons in an atom and the number of bonds that will be formed to reach an octet. Group 18 elements, such as argon and helium, have filled electron configurations and thus rarely participate in chemical bonding. However, atoms from group 17, such as...
14.3K
Electron Affinity03:07

Electron Affinity

35.5K
The electron affinity (EA) is the energy change for adding an electron to a gaseous atom to form an anion (negative ion).
35.5K

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

Unraveling Water-Defect Coupled Degradation via Deuterium Isotope Labeling in Prussian Blue Analogue Cathodes for Long-Life Sodium-Ion Batteries.

Angewandte Chemie (International ed. in English)·2026
Same author

qNEP: A Highly Efficient Neuroevolution Potential with Dynamic Charges for Large-Scale Atomistic Simulations.

Journal of chemical theory and computation·2026
Same author

Operando Observation of Inter-Particle Li<sup>+</sup> Transport in Layered Bimetallic Sulfides for High-Rate Lithium-Sulfur Batteries.

Advanced materials (Deerfield Beach, Fla.)·2026
Same author

Phosphine and Arsine MOFs with Stabilized Diosmium(I) Carbonyl Sawhorse Pillars.

Inorganic chemistry·2025
Same author

Enzyme-Click Postsynthetic Modification of Covalent Organic Frameworks for Photocatalytic H<sub>2</sub>O<sub>2</sub> Production.

Journal of the American Chemical Society·2025
Same author

Learning from Metal Nanocrystal Heterogeneity: A Need for Information-Rich and High-Throughput Single-Nanocrystal Measurements.

ACS nanoscience Au·2025
Same journal

Knowledge Distillation of a Protein Language Model Yields a Foundational Implicit Solvent Model.

Journal of chemical theory and computation·2026
Same journal

Generalizable Protein Folding Pathway Exploration with DA2-GRASP: Extending Beyond Miniproteins.

Journal of chemical theory and computation·2026
Same journal

Improving PCM in Protic Media: Markov State Models for TD-DFT Calculations.

Journal of chemical theory and computation·2026
Same journal

Efficient Coupled-Cluster Python Frameworks for Next-Generation GPUs: A Comparative Study of CuPy and PyTorch on the Hopper and Grace Hopper Architecture.

Journal of chemical theory and computation·2026
Same journal

Extending the MARTINI 3 Coarse-Grained Force Field to Polypeptoids.

Journal of chemical theory and computation·2026
Same journal

Statistical Mechanics of Density- and Temperature-Dependent Potentials: Application to Condensed Phases within GenDPDE.

Journal of chemical theory and computation·2026
查看所有相关文章

相关实验视频

Updated: Jul 2, 2025

Excitonic Hamiltonians for Calculating Optical Absorption Spectra and Optoelectronic Properties of Molecular Aggregates and Solids
08:04

Excitonic Hamiltonians for Calculating Optical Absorption Spectra and Optoelectronic Properties of Molecular Aggregates and Solids

Published on: May 27, 2020

8.4K

电荷优化静电相互作用原子中心神经网络算法

Zichen Song1,2, Jian Han2, Graeme Henkelman3,4

  • 1Shenzhen Key Laboratory of Micro/Nano-Porous Functional Materials (SKLPM), Department of Materials Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China.

Journal of chemical theory and computation
|February 21, 2024
PubMed
概括
此摘要是机器生成的。

本研究引入了一种新的以原子为中心的神经网络 (ANN) 算法,用于预测机器学习潜力的部分电荷和静电相互作用,消除了对参考电荷的需求,并提高了模型可靠性.

更多相关视频

Targeting Neuronal Fiber Tracts for Deep Brain Stimulation Therapy Using Interactive, Patient-Specific Models
14:14

Targeting Neuronal Fiber Tracts for Deep Brain Stimulation Therapy Using Interactive, Patient-Specific Models

Published on: August 12, 2018

8.9K
A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions
07:34

A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions

Published on: March 25, 2014

9.9K

相关实验视频

Last Updated: Jul 2, 2025

Excitonic Hamiltonians for Calculating Optical Absorption Spectra and Optoelectronic Properties of Molecular Aggregates and Solids
08:04

Excitonic Hamiltonians for Calculating Optical Absorption Spectra and Optoelectronic Properties of Molecular Aggregates and Solids

Published on: May 27, 2020

8.4K
Targeting Neuronal Fiber Tracts for Deep Brain Stimulation Therapy Using Interactive, Patient-Specific Models
14:14

Targeting Neuronal Fiber Tracts for Deep Brain Stimulation Therapy Using Interactive, Patient-Specific Models

Published on: August 12, 2018

8.9K
A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions
07:34

A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions

Published on: March 25, 2014

9.9K

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.
  • 机器学习 机器学习

背景情况:

  • 机器学习潜能通常使用部分电荷来建模静电相互作用.
  • 现有的方法往往需要预训练模型和参考电荷,增加复杂性和限制准确性.
  • 电荷分区方法可以是系统依赖的,影响模型可靠性.

研究的目的:

  • 开发一种自相一致的机器学习算法,用于在没有参考数据的情况下预测原子能和电荷.
  • 将这些原子电荷集成到力场模型中,以便准确的静电相互作用计算.
  • 在各种基准系统上评估算法的性能.

主要方法:

  • 开发了一种以原子为中心的神经网络 (ANN) 算法,每个元素只需要一个模型.
  • 该ANN预测了原子能和部分电荷,这些电荷用于通过Ewald总和计算静电能.
  • 使用总能量,力和静电能量训练力场模型.

主要成果:

  • 该ANN算法证明了部分电荷和静电相互作用的合理准确预测.
  • 该方法在Ge板,TiO2晶体和Pd-O纳米粒子系统上进行了测试.
  • 该方法提供了一个自相一致的充电预测策略.

结论:

  • 拟议的ANN算法为机器学习潜力中的静电相互作用建模提供了一种强大而可靠的方法.
  • 这种方法通过消除对参考电荷的依赖来简化力场的开发.
  • 自相一致的电荷预测提高了机器学习在材料科学中的适用性.