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相关概念视频

Catalysis02:50

Catalysis

30.1K
The presence of a catalyst affects the rate of a chemical reaction. A catalyst is a substance that can increase the reaction rate without being consumed during the process. A basic comprehension of a catalysts’ role during chemical reactions can be understood from the concept of reaction mechanisms and energy diagrams.
30.1K
Reduction of Alkenes: Catalytic Hydrogenation02:13

Reduction of Alkenes: Catalytic Hydrogenation

13.9K
Alkenes undergo reduction by the addition of molecular hydrogen to give alkanes. Because the process generally occurs in the presence of a transition-metal catalyst, the reaction is called catalytic hydrogenation.
Metals like palladium, platinum, and nickel are commonly used in their solid forms — fine powder on an inert surface. As these catalysts remain insoluble in the reaction mixture, they are referred to as heterogeneous catalysts.
The hydrogenation process takes place on the...
13.9K
Reduction of Alkenes: Asymmetric Catalytic Hydrogenation02:17

Reduction of Alkenes: Asymmetric Catalytic Hydrogenation

3.8K
Catalytic hydrogenation of alkenes is a transition-metal catalyzed reduction of the double bond using molecular hydrogen to give alkanes. The mode of hydrogen addition follows syn stereochemistry.
The metal catalyst used can be either heterogeneous or homogeneous. When hydrogenation of an alkene generates a chiral center, a pair of enantiomeric products is expected to form. However, an enantiomeric excess of one of the products can be facilitated using an enantioselective reaction or an...
3.8K
Oxidation of Alkenes: Syn Dihydroxylation with Potassium Permanganate02:21

Oxidation of Alkenes: Syn Dihydroxylation with Potassium Permanganate

16.3K
Alkenes can be dihydroxylated using potassium permanganate.  The method encompasses the reaction of an alkene with a cold, dilute solution of potassium permanganate under basic conditions to form a cis-diol along with a brown precipitate of manganese dioxide.
16.3K
Radical Autoxidation01:20

Radical Autoxidation

3.1K
The oxidation of an organic compound in the presence of air or oxygen is called autoxidation. For example, cumene reacts with oxygen to form hydroperoxide. Autoxidation involves initiation, propagation, and termination steps. Many organic compounds are susceptible to autoxidation—especially ethers in the presence of oxygen, which form hydroperoxides. Even though this reaction is slow, old ether bottles contain small amounts of peroxide, which leads to laboratory explosions during ether...
3.1K
Oxidation of Alkenes: Syn Dihydroxylation with Osmium Tetraoxide02:44

Oxidation of Alkenes: Syn Dihydroxylation with Osmium Tetraoxide

12.6K
Alkenes are converted to 1,2-diols or glycols through a process called dihydroxylation. It involves the addition of two hydroxyl groups across the double bond with two different stereochemical approaches, namely anti and syn. Dihydroxylation using osmium tetroxide progresses with syn stereochemistry.
12.6K

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相关实验视频

Updated: Jan 14, 2026

Temperature-programmed Deoxygenation of Acetic Acid on Molybdenum Carbide Catalysts
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Temperature-programmed Deoxygenation of Acetic Acid on Molybdenum Carbide Catalysts

Published on: February 7, 2017

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机器学习驱动的单原子催化剂中介先进氧化过程的全球优化.

Wenjie Gao1, Yongsheng Xu2, Xianglin Chang1

  • 1School of Environmental Science and Engineering/Tianjin Research Center for Safe Disposal of Organic Solid Waste and Energy Utilization Engineering, Tianjin University, Tianjin 300072, China.

Environmental science & technology
|October 18, 2025
PubMed
概括

机器学习准确地预测了通过先进的氧化过程来净化水的单原子催化剂性能. 最佳的催化剂将特定的金属电子数与低电子负性协调相结合,增强污染物降解.

关键词:
一个AOPs的OPs.污染物特性 污染物特性d 电子 d 电子 d 电子机器学习是机器学习.一个原子的催化剂.

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Synthesis and Performance Characterizations of Transition Metal Single Atom Catalyst for Electrochemical CO2 Reduction
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Synthesis and Performance Characterizations of Transition Metal Single Atom Catalyst for Electrochemical CO2 Reduction
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科学领域:

  • 环境化学环境化学
  • 材料科学 材料科学 材料科学
  • 计算化学的计算化学

背景情况:

  • 单原子催化剂 (SAC) 在净化水中的先进氧化过程 (AOP) 中至关重要.
  • 对催化剂特性和污染物特性对AOPs的综合影响的理解是有限的.
  • 预测污染物降解的SAC性能需要综合分析.

研究的目的:

  • 开发一种机器学习模型,用于预测AOP中的SAC性能.
  • 确定影响AOP动力学和热力学的关键描述因素.
  • 为了指导水净化SAC的智能设计.

主要方法:

  • 利用随机森林模型与全球优化策略.
  • 确定了关键描述符:中心金属d电子数和协调环境的电负性.
  • 进行理论计算 (电荷密度,吸附能量,DOS,COHP) 来分析反应机制.

主要成果:

  • ML模型准确地预测了污染物降解性能.
  • d电子数 (5-7) 和平均电子阴性 (<3.04) 是最佳SAC的关键.
  • 污染物特性 (能量差距<3.92 eV,二极矩>7 D) 也对降解产生重大影响.

结论:

  • 机器学习为AOPs设计高性能SAC提供了有效的途径.
  • 优化的SAC可以通过调整金属和协调环境属性来设计.
  • 这种方法有助于开发先进的净水系统.