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相关概念视频

Solubility Equilibria: Overview01:09

Solubility Equilibria: Overview

628
When a substance such as sodium chloride is added to water, it dissolves, forming an aqueous solution. The extent of dissolution is called solubility. The process of dissolution can exist in equilibrium, just like other chemical processes. Solubility equilibria are also called precipitation equilibria because the process of solubility can be reversible. The reverse of the solubility process is called precipitation.
Solubility is important in biological and environmental processes. A notable...
628
Solution Formation02:16

Solution Formation

31.4K
There is no one solvent that can dissolve every type of solute. Some substances that readily dissolve in a certain solvent might be insoluble in a different solvent. A simple way to predict which substances dissolve in which solvent is the phrase "like dissolves like". This means that polar substances, such as salt and sugar, dissolve in a polar substance like water. In contrast, non-polar substances are more soluble in non-polar solvents such as carbon tetrachloride.
This selective...
31.4K
Solubility Equilibria03:07

Solubility Equilibria

52.4K
Solubility equilibria are established when the dissolution and precipitation of a solute species occur at equal rates. These equilibria underlie many natural and technological processes, ranging from tooth decay to water purification. An understanding of the factors affecting compound solubility is, therefore, essential to the effective management of these processes. This section applies previously introduced equilibrium concepts and tools to systems involving dissolution and precipitation.
The...
52.4K
Factors Affecting Solubility04:01

Factors Affecting Solubility

33.3K
Compared with pure water, the solubility of an ionic compound is less in aqueous solutions containing a common ion (one also produced by dissolution of the ionic compound). This is an example of a phenomenon known as the common ion effect, which is a consequence of the law of mass action that may be explained using Le Chȃtelier’s principle. Consider the dissolution of silver iodide:
33.3K
Factors Affecting Dissolution: Drug pKa, Lipophilicity and GI pH01:21

Factors Affecting Dissolution: Drug pKa, Lipophilicity and GI pH

1.2K
Drug absorption within the gastrointestinal (GI) tract is a complex process influenced by several critical factors, including the site pH, the drug's dissociation constant (pKa), and the drug's lipophilicity. The GI tract exhibits a pH gradient, with an acidic environment in the stomach and a more alkaline environment in the small intestine. This pH variation directly affects the ionization state of drugs.
A drug's pKa and the pH of the gastrointestinal (GI) tract play crucial roles...
1.2K
Theories of Dissolution: The Danckwerts' Model and Interfacial Barrier Model01:09

Theories of Dissolution: The Danckwerts' Model and Interfacial Barrier Model

278
Various dissolution theories provide insight into the factors that influence the dissolution rate. Danckwerts' Model suggests that turbulence, rather than a stagnant layer, characterizes the dissolution medium at the solid-liquid interface. In this model, the agitated solvent contains macroscopic packets that move to the interface via eddy currents, facilitating the absorption and delivery of the drug to the bulk solution. The regular replenishment of solvent packets maintains the...
278

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相关实验视频

Updated: Jun 16, 2025

Solubility of Hydrophobic Compounds in Aqueous Solution Using Combinations of Self-assembling Peptide and Amino Acid
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Solubility of Hydrophobic Compounds in Aqueous Solution Using Combinations of Self-assembling Peptide and Amino Acid

Published on: September 20, 2017

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重新审视机器学习方法在预测水溶性中的应用.

Tianyuan Zheng1, John B O Mitchell2, Simon Dobson1

  • 1School of Computer Science, University of St Andrews, St Andrews, Fife KY16 9SX, U.K.

ACS omega
|August 19, 2024
PubMed
概括

预测化学物质的水溶性对于许多行业至关重要. 这项研究比较了机器学习模型,发现基于图的方法在清洁数据中表现出色,而分子描述器为溶解性预测提供了更好的解释性和噪声弹性.

科学领域:

  • 计算化学计算化学
  • 药物发现 药物发现 药物发现
  • 环境科学 环境科学

背景情况:

  • 准确预测水溶性在制药,环境和农业化学领域至关重要.
  • 尽管它很重要,但准确预测化学溶解度仍然是一个重大的科学挑战.
  • 机器学习和分子描述器为改善可溶性预测提供了有希望的途径.

研究的目的:

  • 评估和比较流行的机器学习 (ML) 方法来预测水溶性.
  • 在ML模型中评估各种分子特征化技术的有效性.
  • 识别关键的分子描述符,有助于准确的溶解性预测.

主要方法:

  • 对各种机器学习算法的比较分析.
  • 实施各种分子特征化技术,包括图形卷曲和注意力机制.
  • 评估了4000多个分子描述符的预测性贡献.

主要成果:

  • 基于图形的ML方法在高质量的数据集上显示出异常的预测能力.
  • 使用分子描述器的模型表现出优越的解释性和对数据噪声的弹性.
  • 在分析的4000个分子描述符中,大约有800个被发现对溶解度预测具有重要意义.

更多相关视频

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
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Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

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Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA
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Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA

Published on: February 23, 2024

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相关实验视频

Last Updated: Jun 16, 2025

Solubility of Hydrophobic Compounds in Aqueous Solution Using Combinations of Self-assembling Peptide and Amino Acid
05:08

Solubility of Hydrophobic Compounds in Aqueous Solution Using Combinations of Self-assembling Peptide and Amino Acid

Published on: September 20, 2017

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Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
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Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

Published on: January 26, 2024

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Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA
10:21

Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA

Published on: February 23, 2024

2.4K

结论:

  • 机器学习模型在水溶性预测方面提供了显著的改进.
  • 选择ML方法和特色化技术会影响性能和可解释性.
  • 未来的研究应该专注于强大的描述器选择和噪声强大的建模,以提高可溶性预测.