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

Atomic Absorption Spectroscopy: Overview01:27

Atomic Absorption Spectroscopy: Overview

1.5K
Atomic absorption spectroscopy (AAS) is a technique used to analyze elements by measuring electromagnetic radiation (EMR) absorbed by atoms, which causes them to transition to a higher-energy orbit. The most crucial step in AAS is atomization, where the analyte is converted into gas-phase atoms, typically through a flame or furnace. Some of these atoms become thermally excited in the flame, while most remain in the ground state.
When irradiated by EMR of a particular wavelength, these...
1.5K
Atomic Orbitals02:44

Atomic Orbitals

33.2K
An atomic orbital represents the three-dimensional regions in an atom where an electron has the highest probability to reside. The radial distribution function indicates the total probability of finding an electron within the thin shell at a distance r from the nucleus. The atomic orbitals have distinct shapes which are determined by l, the angular momentum quantum number. The orbitals are often drawn with a boundary surface, enclosing densest regions of the cloud.
33.2K
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
Molecular Orbital Theory II03:51

Molecular Orbital Theory II

19.0K
Molecular Orbital Energy Diagrams
19.0K
Atomic Absorption Spectroscopy: Atomization Methods01:25

Atomic Absorption Spectroscopy: Atomization Methods

373
Atomic Absorption Spectroscopy (AAS) atomizes samples through flame atomization or electrothermal atomization. Flame atomization typically involves a nebulizer and spray chamber assembly to combine the sample with a fuel–oxidant mixture, creating a fine aerosol mist that enters a burner. Typically, the fuel and oxidant are combined in an approximately stoichiometric ratio. However, for atoms that are easily oxidized, a fuel-rich mixture may be more advantageous. Only about 5% of the...
373
Correlations02:20

Correlations

32.7K
Correlation means that there is a relationship between two or more variables (such as ice cream consumption and crime), but this relationship does not necessarily imply cause and effect. When two variables are correlated, it simply means that as one variable changes, so does the other. We can measure correlation by calculating a statistic known as a correlation coefficient. A correlation coefficient is a number from -1 to +1 that indicates the strength and direction of the relationship between...
32.7K

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

tmQMg* Data Set: Excited State Properties of 74k Transition Metal Complexes.

Journal of chemical information and modeling·2025
Same author

Diving deep into zeolite space.

Nature computational science·2025
Same author

AI Approaches to Homogeneous Catalysis with Transition Metal Complexes.

ACS catalysis·2025
Same author

Metal-Dependent Mechanism of the Electrocatalytic Reduction of CO<sub>2</sub> by Bipyridine Complexes Bearing Pendant Amines: A DFT Study.

ACS organic & inorganic Au·2025
Same author

Copper(II)-Oxyl Formation in a Biomimetic Complex Activated by Hydrogen Peroxide: The Key Role of Trans-Bis(Hydroxo) Species.

Inorganic chemistry·2024
Same author

Augmenting genetic algorithms with machine learning for inverse molecular design.

Chemical science·2024
Same journal

Mapping Evolution of Molecules across Biochemistry with Assembly Theory.

Journal of chemical information and modeling·2026
Same journal

Structural Proteomics-Based Deciphering of Hydrophobic Packing Fingerprints Informing Protein Thermostability in TIM Barrels.

Journal of chemical information and modeling·2026
Same journal

Bridging between Structure-Based and Data-Driven Affinity Prediction.

Journal of chemical information and modeling·2026
Same journal

Reinforcement Learning-Driven Multiproperty Optimization in Molecular Design Using Multicontext Transcriptome Data.

Journal of chemical information and modeling·2026
Same journal

EnsembleCycPerm: Interpretable Modeling of Cyclic Peptide Permeability through Solvent-Dependent Conformational Ensembles.

Journal of chemical information and modeling·2026
Same journal

Resolving Conformational Preferences of Monosaccharides from <sup>1</sup>H and <sup>13</sup>C NMR Chemical Shifts Using an Integrated MD and QM Approach.

Journal of chemical information and modeling·2026
查看所有相关文章

相关实验视频

Updated: Jun 6, 2025

Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis
07:11

Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis

Published on: November 10, 2023

2.2K

亚巴巴图核:用于机器学习的原子-原子,债券-债券和债券-原子自相对应.

Lucía Morán-González1,2, Jørn Eirik Betten3, Hannes Kneiding1

  • 1Hylleraas Centre for Quantum Molecular Sciences, Department of Chemistry, University of Oslo, P.O. Box 1033 0315 Oslo, Norway.

Journal of chemical information and modeling
|November 24, 2024
PubMed
概括
此摘要是机器生成的。

一个新的图核,原子-原子,键-键和键-原子 (AABBA) 自相对应,增强了机器学习的分子表示. 这种方法优于现有的方法,用于预测复杂的过渡金属复合物的特性.

更多相关视频

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

8.1K
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

相关实验视频

Last Updated: Jun 6, 2025

Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis
07:11

Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis

Published on: November 10, 2023

2.2K
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

8.1K
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

科学领域:

  • 计算化学的计算化学
  • 机器学习 机器学习
  • 化学信息学 化学信息学

背景情况:

  • 分子图是化学结构的强大表示.
  • 图核将分子图形转化为用于机器学习的矢量.
  • 现有的图核主要集中在原子节点上.

研究的目的:

  • 开发一个新的图核,包含原子-原子,键-键和键-原子 (AABBA) 自相对应.
  • 评估AABBA内核在涉及过渡金属复合物的回归任务中的性能.
  • 通过考虑原子和键性质来改进分子表示.

主要方法:

  • 开发了 AABBA 图形内核.
  • 应用了内核来生成分子图的矢量表示.
  • 测试了回归机器学习任务的表示,包括预测Vaska复合体的能量障碍和键距离.
  • 利用各种机器学习模型,如神经网络,梯度增强机器和高斯过程.

主要成果:

  • 与基线方法相比,AABBA图核显示出更高的性能 (仅限原子对原子自相对应).
  • 缩小尺寸显示,债券-债券和债券-原子自相关性对特征相关性有很大贡献.
  • 亚巴巴核能有效预测过渡金属复合物的能量障碍和键距离.

结论:

  • 通过整合原子和键性质,AABBA图核提供了更全面的分子表示.
  • 这种新的方法可以加速对大型化学空间的探索.
  • AABBA内核为开发利用原子和键信息的新分子表示提供了基础.