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相关概念视频

Preparation of Amines: Reductive Amination of Aldehydes and Ketones01:38

Preparation of Amines: Reductive Amination of Aldehydes and Ketones

3.2K
Carbonyl compounds and primary amines undergo reductive amination first to produce imines, followed by secondary amines in the same reaction mixture, using selective reducing agents like sodium cyanoborohydride or sodium triacetoxyborohydride. Reductive amination produces different degrees of substitution of amines depending on the starting amine substrate.
3.2K
Amides to Amines: LiAlH4 Reduction01:20

Amides to Amines: LiAlH4 Reduction

5.1K
Amide reduction with strong reducing agents like lithium aluminum hydride proceeds through a nucleophilic acyl substitution to form amines. Primary, secondary, and tertiary amides yield primary, secondary, and tertiary amines, respectively.
Amide reduction requires two equivalents of the reducing agent, acting as a source of hydride ions. As shown in the figure, the reaction is initiated with a nucleophilic attack by the hydride ion at the carbonyl carbon to form a tetrahedral intermediate.
5.1K
Cycloaddition Reactions: MO Requirements for Photochemical Activation01:12

Cycloaddition Reactions: MO Requirements for Photochemical Activation

2.2K
Some cycloaddition reactions are activated by heat, while others are initiated by light. For example, a [2 + 2] cycloaddition between two ethylene molecules occurs only in the presence of light. It is photochemically allowed but thermally forbidden.
2.2K
Preparation of Amines: Reduction of Oximes and Nitro Compounds01:29

Preparation of Amines: Reduction of Oximes and Nitro Compounds

4.1K
Oximes can be reduced to primary amines using catalytic hydrogenation, hydride reduction, or sodium metal reduction. The reduction of aliphatic and aromatic nitro compounds to primary amines takes place by either catalytic hydrogenation or by using active metals like Fe, Zn, and Sn in the presence of an acid.
Though catalytic hydrogenation can reduce nitrobenzenes, the reduction is nonselective in the presence of other functional groups. For instance, if nitrobenzene contains an aldehyde group,...
4.1K
Oxymercuration-Reduction of Alkenes02:36

Oxymercuration-Reduction of Alkenes

8.0K
Oxymercuration–reduction of alkenes is one of the major reactions converting alkenes to alcohols. It involves the hydration of alkenes with mercuric acetate in a mixture of tetrahydrofuran and water, forming an organomercury adduct. This is followed by a demercuration step in which the adduct is reduced to an alcohol using sodium borohydride.
8.0K
Nitriles to Amines: LiAlH4 Reduction00:55

Nitriles to Amines: LiAlH4 Reduction

3.8K
Nitriles are reduced to amines in the presence of strong reducing agents like lithium aluminum hydride through a typical nucleophilic acyl substitution. The reaction requires two equivalents of the reducing agent. The reducing agent acts as a source of hydride ions.
As shown below, the mechanism involves three steps. Firstly, the hydride ion acting as a nucleophile attacks the nitrile carbon to form an anion. In the second step, a second equivalent of the hydride ion attacks the anion to...
3.8K

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相关实验视频

Updated: Sep 18, 2025

Continuous Flow Chemistry: Reaction of Diphenyldiazomethane with p-Nitrobenzoic Acid
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机器学习驱动的优化连续流光反胺合成的光反胺合成.

Perman Jorayev1,2, Sebastian Soritz1,3, Simon Sung2

  • 1Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge CB3 0AS, United Kingdom.

Organic process research & development
|June 26, 2025
PubMed
概括

机器学习优化了光电还原催化技术,用于合成三级胺. 与传统的批量方法相比,这种方法显著提高了反应效率和吞吐量,使得药物发现速度更快.

关键词:
贝叶斯优化是贝叶斯的优化.自动化自动化自动化自动化流动化学 流动化学摄影氧化物化学

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科学领域:

  • 有机化学 有机化学
  • 催化剂是一种催化剂.
  • 化学工程是化学工程的重要组成部分.

背景情况:

  • 光电氧催化对于合成具有药学意义的C- ((sp3) 丰富的三级胺来说至关重要.
  • 优化这些反应是具有挑战性的,因为复杂的机械模型和巨大的反应空间.

研究的目的:

  • 为了证明光氧三级胺合成的机器学习驱动优化.
  • 为了确定关键的反应参数,并在连续流设置中提高工艺稳定性.

主要方法:

  • 使用半自动连续流设置,有六个连续变量和一个离散变量.
  • 采用先验知识生成 (例如,可溶性预测) 和贝叶斯优化算法 (NEMO).
  • 分析结果使用换特征重要性和部分依赖图.

主要成果:

  • 确定了影响产量和成本的关键参数,包括催化剂负载,停留时间和溶剂选择.
  • 发现了催化剂负荷,停留时间和吸收光子等价性之间的相关性.
  • 实现的吞吐量大约是批量反应的25倍,达到~12g/day.

结论:

  • 机器学习,特别是NEMO,有效地优化复杂的光反反应.
  • 连续流合成为三级氨基合成提供了相对于批量工艺的显著生产力提升.
  • 开发的工作流加速了发现和优化有价值的制药中间体.