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

Electron Configurations02:46

Electron Configurations

16.6K
Electron configurations and orbital diagrams can be determined by applying the Aufbau principle (each added electron occupies the subshell of lowest energy available), Pauli exclusion principle (no two electrons can have the same set of four quantum numbers), and Hund’s rule of maximum multiplicity (whenever possible, electrons retain unpaired spins in degenerate orbitals).
The relative energies of the subshells determine the order in which atomic orbitals are filled (1s, 2s, 2p, 3s, 3p,...
16.6K
Van der Waals Equation01:10

Van der Waals Equation

4.0K
The ideal gas law is an approximation that works well at high temperatures and low pressures. The van der Waals equation of state (named after the Dutch physicist Johannes van der Waals, 1837−1923) improves it by considering two factors.
First, the attractive forces between molecules, which are stronger at higher densities and reduce the pressure, are considered by adding to the pressure a term equal to the square of the molar density multiplied by a positive coefficient a. Second, the volume...
4.0K
Electronic Structure of Atoms02:28

Electronic Structure of Atoms

21.3K

An atom comprises protons and neutrons, which are contained inside the dense, central core called the nucleus, with electrons present around the nucleus. Taking into account the wave–particle duality of electrons and the uncertainty in position around the nucleus, quantum mechanics provides a more accurate model for the atomic structure. It describes atomic orbitals as the regions around the nucleus where electrons of discrete energy exist, characterized by four quantum...
21.3K
Electron Configuration of Multielectron Atoms03:26

Electron Configuration of Multielectron Atoms

40.2K
The alkali metal sodium (atomic number 11) has one more electron than the neon atom. This electron must go into the lowest-energy subshell available, the 3s orbital, giving a 1s22s22p63s1 configuration. The electrons occupying the outermost shell orbital(s) (highest value of n) are called valence electrons, and those occupying the inner shell orbitals are called core electrons. Since the core electron shells correspond to noble gas electron configurations, we can abbreviate electron...
40.2K
Electron Orbital Model01:18

Electron Orbital Model

67.7K
Orbitals are the areas outside of the atomic nucleus where electrons are most likely to reside. They are characterized by different energy levels, shapes, and three-dimensional orientations. The location of electrons is described most generally by a shell or principal energy level, then by a subshell within each shell, and finally, by individual orbitals found within the subshells.
The first shell is closest to the nucleus, and it has only one subshell with a single spherical orbital called the...
67.7K
Valence Bond Theory and Hybridized Orbitals02:38

Valence Bond Theory and Hybridized Orbitals

19.3K
According to valence bond theory, a covalent bond results when: (1) an orbital on one atom overlaps an orbital on a second atom, and (2) the single electrons in each orbital combine to form an electron pair. The strength of a covalent bond depends on the extent of overlap of the orbitals involved. Maximum overlap is possible when the orbitals overlap on a direct line between the two nuclei.
A σ bond (single bond in a Lewis structure) is a covalent bond in which the electron density is...
19.3K

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

Charged Defects in UO<sub>2</sub> Bulk and Surface: A First-Principles Study.

ACS applied materials & interfaces·2026
Same author

Isolation of an Americium Complex Containing a Radical Ligand.

Journal of the American Chemical Society·2026
Same author

Augmenting Large Language Models for Automated Discovery of F-Element Extractants.

Journal of the American Chemical Society·2026
Same author

Probing <i>f</i>-Block Covalency at the Limits of Hard-Metal/Soft-Ligand Interactions through Chalcogenoether Complexes.

Journal of the American Chemical Society·2025
Same author

Combining Reactive Quantum-Mechanical Molecular-Dynamics Simulations with Mutagenesis, Crystallography, and Enzyme Kinetics to Reveal Plausible Steps of Isocyanide Hydratase Catalysis.

Journal of chemical information and modeling·2025
Same author

Data-Driven Kinetic Reaction Networks for Separation Chemistry.

Journal of chemical theory and computation·2025
Same journal

Complementing Onsager's Conductivity Theory by Grotthuss Mechanism Mitigation via Ion-Induced Depletion of Hydrogen-Bond-Donating Water.

Journal of chemical theory and computation·2026
Same journal

Microscopic Stress in Biomembranes: A Perspective on Key Concepts, Methods, and Applications.

Journal of chemical theory and computation·2026
Same journal

Analytic Nuclear Gradients Including Oriented External Electric Fields in a Molecule-Fixed Frame.

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

相关实验视频

Updated: Jun 21, 2025

Atomic Layer Deposition of Vanadium Dioxide and a Temperature-dependent Optical Model
11:10

Atomic Layer Deposition of Vanadium Dioxide and a Temperature-dependent Optical Model

Published on: May 23, 2018

11.9K

对于5f-元素的密度功能紧密结合的有效参数化:一个Th-O案例研究.

Chang Liu1, Néstor F Aguirre1, Marc J Cawkwell1

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

Journal of chemical theory and computation
|July 11, 2024
PubMed
概括
此摘要是机器生成的。

对f元素进行密度函数紧密结合 (DFTB) 模型的参数化在计算上是昂贵的. 本研究介绍了有效的方法,包括按轨道组进行校正和加速优化,以减少f元素DFTB模型的参数和计算成本.

更多相关视频

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

5.7K
Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry
12:11

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

Published on: April 8, 2020

8.2K

相关实验视频

Last Updated: Jun 21, 2025

Atomic Layer Deposition of Vanadium Dioxide and a Temperature-dependent Optical Model
11:10

Atomic Layer Deposition of Vanadium Dioxide and a Temperature-dependent Optical Model

Published on: May 23, 2018

11.9K
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

5.7K
Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry
12:11

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

Published on: April 8, 2020

8.2K

科学领域:

  • 计算化学计算化学
  • 材料科学 材料科学 材料科学
  • 量子化学 是一个量子化学.

背景情况:

  • 对f元素物种的密度功能紧密结合 (DFTB) 模型进行参数化是具有挑战性的,因为有大量可调节的参数.
  • 参数优化的计算成本随着轨道数的增加而增加,这使得f元素与主要组元素相比变得昂贵.
  • 准确的f元素的DFTB哈密尔顿数对于理解它们在结合相互作用中的作用至关重要.

研究的目的:

  • 开发有效的方法来缓解DFTB对f元素的参数化中的大型参数空间挑战.
  • 为了减少参数数量和计算成本,同时保持f元素DFTB模型的准确性.
  • 为Th-O系统参数化DFTB哈密尔顿式,并将其应用于研究ThO2纳米粒子.

主要方法:

  • 开发了对两中心键积的新型组对轨道校正函数,以与元素数线性地减少参数.
  • 对于较大的训练集,使用小批量布罗伊登弗莱彻戈德法尔布沙诺 (BFGS) 方法加速参数优化.
  • 在目标函数中使用一个随机优化器来克服局部最小值.

主要成果:

  • 在保持精度的同时,将f元素的参数数量减少了40%以上.
  • 通过使用大型训练集 (6322个结构) 成功对Th-O系统的DFTB哈密尔顿式进行了参数化.
  • 优化的参数集 (LANL-ThO) 与对集群和批量ThO2的DFT计算属性有很好的一致性.

结论:

  • 提出的高效方法显著降低了f元素的DFTB参数化计算成本和参数数量.
  • 这种方法显示出具有挑战性的DFTB参数化任务的潜力,涉及具有高角度动量元素.
  • LANL-ThO参数集为研究ThO2纳米粒子和相关系统提供了可靠的工具.