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相关概念视频

Acid and Bases: Ka, pKa, and Relative Strengths02:35

Acid and Bases: Ka, pKa, and Relative Strengths

26.0K
This lesson delves into a critical aspect of the relative strengths of acids and bases. The strength of an acid is evaluated by the acid dissociation into its conjugate base and a hydronium ion in water. The complete dissociation of a strong acid is confirmed with a very high concentration of hydronium ions. As a result, an incomplete dissociation process affirms a weak acid. Therefore, the equilibrium is in the forward direction for strong acids and backward for weak acids in these reactions.
26.0K
Basicity of Aliphatic Amines01:21

Basicity of Aliphatic Amines

5.7K
Amines can behave as Brønsted–Lowry bases by accepting a proton from the acid to form corresponding conjugate acids. Due to a lone pair of nonbonding electrons, aliphatic amines can also act as Lewis bases by forming a covalent bond with an electrophile.
To measure the basicity of amines, two conventions are generally used. The first defines Kb as the basicity constant for the deprotonation reaction of water by the amine, as presented in Figure 1. Conventionally, lower Kb indicates...
5.7K
Acidity of Carboxylic Acids01:21

Acidity of Carboxylic Acids

6.7K
Carboxylic acids are the strongest organic acids. However, their acidic strength is much less than mineral acids like HCl. Carboxylic acids ionize in water and readily lose the hydroxyl proton to form a resonance-stabilized carboxylate ion.
6.7K
Acidity of 1-Alkynes02:42

Acidity of 1-Alkynes

9.5K

The acidic strength of hydrocarbons follows the order: Alkynes > Alkenes > Alkanes. The strength of an acid is commonly expressed in units of pKa — the lower the pKa, the stronger the acid. Among the hydrocarbons, terminal alkynes have lower pKa values and are, therefore, more acidic. For example, the pKa values for ethane, ethene, and acetylene are 51, 44, and 25, respectively, as shown here.
9.5K
Molecular Structure and Acidity02:34

Molecular Structure and Acidity

16.8K
An acid can be deprotonated to form a conjugate base or an anion. If the produced anion is more stable, then the acid is stronger. On the contrary, if the anion is unstable, then the acid is weaker. Hence, to determine the acidity of the compound, the stability of its conjugate base is studied using various factors.
The size effect explains the change in atomic size on acidity. When comparing the acids formed from elements that belong to the same column in the periodic table, their atomic sizes...
16.8K
Relative Strengths of Conjugate Acid-Base Pairs02:29

Relative Strengths of Conjugate Acid-Base Pairs

45.2K
Brønsted-Lowry acid-base chemistry is the transfer of protons; thus, logic suggests a relation between the relative strengths of conjugate acid-base pairs. The strength of an acid or base is quantified in its ionization constant, Ka or Kb, which represents the extent of the acid or base ionization reaction. For the conjugate acid-base pair HA / A−, the ionization equilibrium equations and ionization constant expressions are
45.2K

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Determination of the Gas-phase Acidities of Oligopeptides
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对酸的pKa预测进行比较分析,使用密度函数理论和机器学习方法.

Miroslava Nedyalkova1,2,3, Diana Heredia4, Joaquín Barroso-Flores5,6

  • 1Swiss National Center for Competence in Research (NCCR) Bio-inspired Materials, University of Fribourg, Chemin des Verdiers 4, Fribourg CH-1700, Switzerland.

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概括

准确预测酸电离 (pKa) 对于环境和健康风险评估至关重要. 基于原子电荷的密度函数理论方法和机器学习方法显示了pKa预测最有前途的结果.

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科学领域:

  • 环境化学环境化学
  • 计算化学的计算化学
  • 毒理学 毒理学 毒理学

背景情况:

  • 燃烧酸是环境污染物,具有可变的电离状态,影响其性能和风险.
  • 准确预测酸pKa是必不可少的,但由于现有模型的局限性而具有挑战性.

研究的目的:

  • 用机器学习和密度函数理论模型比较分析pKa预测的准确性.
  • 确定最有效的计算方法来预测酸pKa值.

主要方法:

  • 支持矢量基于机器的机器学习 (ML) 方法.
  • 基于三密度函数理论 (DFT) 的模型:V_S,max,SM D基的原子电荷,以及缩放的溶剂可访问表面.
  • 使用平均无符号错误对预测准确性的比较分析.

主要成果:

  • 缩放的溶剂可访问表面方法显示出高误差,表明效率低.
  • 使用对联火基上的原子电荷的DFT方法提供了最准确的pKa预测.
  • 基于ML的方法显示出强大的预测性能,适用于更广泛的化学应用.
  • V_S,max DFT 方法由于其在捕获分子相互作用方面的范围有限,因此显示出较弱的预测.

结论:

  • 基于原子电荷的DFT方法和ML方法在预测酸pKa时非常有效.
  • 对于pKa预测,V_S,max方法的可靠性较低,因为它过度简化了分子相互作用.
  • 准确的pKa预测对于理解和减轻烧焦酸对环境和健康的风险至关重要.