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

Predicting Reaction Outcomes02:24

Predicting Reaction Outcomes

8.6K
Kinetics describes the rate and path by which a reaction occurs. In contrast, thermodynamics deals with state functions and describes the properties, behavior, and components of a system. It is not concerned with the path taken by the process and cannot address the rate at which a reaction occurs. Although it does provide information about what can happen during a reaction process, it does not describe the detailed steps of what appears on an atomic or a molecular level. On the other hand,...
8.6K
Reaction Yield02:22

Reaction Yield

52.3K
The theoretical yield of a reaction is the amount of product estimated to form based on the stoichiometry of the balanced chemical equation. The theoretical yield assumes the complete conversion of the limiting reactant into the desired product. The amount of product that is obtained by performing the reaction is called the actual yield, and it may be less than or (very rarely) equal to the theoretical yield.
52.3K
Measuring Reaction Rates03:09

Measuring Reaction Rates

25.8K
Polarimetry finds application in chemical kinetics to measure the concentration and reaction kinetics of optically active substances during a chemical reaction. Optically active substances have the capability of rotating the plane of polarization of linearly polarized light passing through them—a feature called optical rotation. Optical activity is attributed to the molecular structure of substances. Normal monochromatic light is unpolarized and possesses oscillations of the electrical...
25.8K
Reaction Quotient02:35

Reaction Quotient

49.1K
The status of a reversible reaction is conveniently assessed by evaluating its reaction quotient (Q). For a reversible reaction described by m A + n B ⇌ x C + y D, the reaction quotient is derived directly from the stoichiometry of the balanced equation as
49.1K
Standard Entropy Change for a Reaction03:00

Standard Entropy Change for a Reaction

21.2K
Entropy is a state function, so the standard entropy change for a chemical reaction (ΔS°rxn) can be calculated from the difference in standard entropy between the products and the reactants.
21.2K
E1 Reaction: Kinetics and Mechanism02:46

E1 Reaction: Kinetics and Mechanism

15.7K
Here, in contrast to the E2 reaction mechanism, we delve into the aspects of the E1 reaction mechanism, which has two steps: rate-limiting loss of the leaving group and abstraction of the beta hydrogen by a weak base. Typically, the experimental proof for the E1 mechanism is via kinetic studies or isotope studies. While the former demonstrates the first-order kinetics—the dependence of the reaction solely on substrate concentration—the latter proves the abstraction of hydrogen only...
15.7K

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

SUDA: Simultaneous unsupervised knowledge distillation and adaptation of foundation models for efficient pathological image analysis.

Medical image analysis·2026
Same author

Heritability of Alzheimer's disease-related plasma biomarkers in the Amish population.

Alzheimer's & dementia (Amsterdam, Netherlands)·2026
Same author

Aromaticity and structure switching of cyclopropametallaindole to metallaquinolinium.

Nature communications·2026
Same author

Association between vitamin D deficiency and adrenal gland, kidney function, indicators related to cardiovascular function in hypertensive patients.

Frontiers in nutrition·2026
Same author

Novel injectable and wet bonding bone adhesive: physicochemical characterization and biocompatibility evaluation.

BMC oral health·2026
Same author

Circadian-immune-related gene signature for lung squamous cell carcinoma: machine learning and multi-omics analysis.

Translational cancer research·2026
Same journal

First Total Synthesis of Cryptolaevilactones, Unique Spiromeroterpenoids.

The Journal of organic chemistry·2026
Same journal

Aza-Friedel-Crafts Cyclization vs Plancher Rearrangement in the Acid-Catalyzed Reaction of 3-Benzylindolenines.

The Journal of organic chemistry·2026
Same journal

From Targeted Synthesis to Serendipitous Discovery: Transforming Perfluorotoluene into Discotic Liquid Crystals and Dearomatized Spirofluorenes.

The Journal of organic chemistry·2026
Same journal

Unveiling the Electronic Effects of Lewis and Brønsted Base Catalysts in Diels-Alder Reactions.

The Journal of organic chemistry·2026
Same journal

The Mechanism of Acid-Catalyzed Decarboxylation of Aromatic <i>o</i>-Hydroxycarboxylic Acids: Insights from <i>o</i>-Hydroxynaphthoic Acids.

The Journal of organic chemistry·2026
Same journal

Organocatalytic Multicomponent Reactions Using 1,1-Diaminobenzalazine: Synthesis of Pyrano[2,3-<i>c</i>]pyrazoles and Pyranochromenes.

The Journal of organic chemistry·2026
查看所有相关文章

相关实验视频

Updated: Sep 9, 2025

Optimization of the Ugi Reaction Using Parallel Synthesis and Automated Liquid Handling
08:24

Optimization of the Ugi Reaction Using Parallel Synthesis and Automated Liquid Handling

Published on: November 11, 2008

16.5K

在具有挑战性的回反应收益率数据集上优化模型学习性能

Shen Wang1,2, Yining Liu1,3, Weiren Zhao1,3

  • 1State Key Laboratory of Fine Chemicals, Dalian University of Technology, Dalian 116024, China.

The Journal of organic chemistry
|September 3, 2025
PubMed
概括
此摘要是机器生成的。

一个新的数据集,HeckLit,帮助机器学习在有机合成. 一个子集分割训练策略 (SSTS) 在这个大数据集上提高了模型性能,提高了ML驱动的反应产量预测.

更多相关视频

A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM
13:54

A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM

Published on: August 18, 2023

4.9K
High-Throughput Metabolic Profiling for Model Refinements of Microalgae
11:07

High-Throughput Metabolic Profiling for Model Refinements of Microalgae

Published on: December 4, 2021

3.9K

相关实验视频

Last Updated: Sep 9, 2025

Optimization of the Ugi Reaction Using Parallel Synthesis and Automated Liquid Handling
08:24

Optimization of the Ugi Reaction Using Parallel Synthesis and Automated Liquid Handling

Published on: November 11, 2008

16.5K
A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM
13:54

A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM

Published on: August 18, 2023

4.9K
High-Throughput Metabolic Profiling for Model Refinements of Microalgae
11:07

High-Throughput Metabolic Profiling for Model Refinements of Microalgae

Published on: December 4, 2021

3.9K

科学领域:

  • 有机化学
  • 机器学习
  • 计算化学

背景情况:

  • 在有机合成中机器学习 (ML) 的发展受到有限的数据可用性阻碍.
  • 现有的基于文献的数据集经常受到稀疏分布和高收益偏差的影响,限制了ML模型的性能.
  • HeckLit数据集包括10002个来自Heck反应的案例,为ML应用提供了广泛的化学空间.

研究的目的:

  • 从文献中建立一个全面的,符合ML的Heck反应产量数据集.
  • 应对文献数据集的数据稀疏性和高产率偏好的挑战.
  • 提高有机合成反应的ML模型的预测精度.

主要方法:

  • 开发了HeckLit数据集,一个由文献挖掘的10,002个Heck反应产量案例的集合.
  • 应用特征分布平滑 (FDS) 来解决数据稀疏性.
  • 实施分组培训策略 (SSTS) 以优化模型学习.
  • 使用R平方 (R2) 度量对模型性能进行评估.

主要成果:

  • HeckLit数据集覆盖了一个广泛的化学空间,比高通量实验数据集大得多.
  • 在HeckLit上初始的ML模型性能为R2=0.318,表明学习能力有限.
  • 特性分布平滑 (FDS) 没有改善模型性能.
  • 部分组分训练策略 (SSTS) 显著提高了模型性能,达到R2=0.380.

结论:

  • HeckLit 数据集为在有机合成中推进ML提供了宝贵的资源.
  • 分组训练策略 (SSTS) 是一种有效的方法,可以在稀疏的文献数据集上提高ML模型的性能.
  • 该研究提出了分组划分的标准,提供了从大规模化学数据中学习的新方法.