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Solubility Equilibria: Ionic Product of Water01:16

Solubility Equilibria: Ionic Product of Water

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Pure water is a weak electrolyte; only a small amount ionizes into hydrogen and hydroxide ions. At any given temperature, the concentration of undissociated water is almost constant, so the ionic product of water is the product of the hydrogen and hydroxide ion concentrations, denoted as Kw. The square root of Kw gives the individual ion concentrations.
The ionic product of water varies with temperature, and its value is 1.0 x 10−14 at standard experimental conditions. Per Le...
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Factors Affecting Solubility04:01

Factors Affecting Solubility

33.9K
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:
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Solubility Equilibria: Overview01:09

Solubility Equilibria: Overview

824
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...
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Solubility of Ionic Compounds02:55

Solubility of Ionic Compounds

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Solubility is the measure of the maximum amount of solute that can be dissolved in a given quantity of solvent at a given temperature and pressure. Solubility is usually measured in molarity (M) or moles per liter (mol/L). A compound is termed soluble if it dissolves in water.
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Solubility Equilibria03:07

Solubility Equilibria

53.2K
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...
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Solubility03:00

Solubility

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Solution, Solubility, and Solubility Equilibrium
A solution is a homogeneous mixture composed of a solvent, the major component, and a solute, the minor component. The physical state of a solution—solid, liquid, or gas—is typically the same as that of the solvent. Solute concentrations are often described with qualitative terms such as dilute (of relatively low concentration) and concentrated (of relatively high concentration).
In a solution, the solute particles (molecules,...
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Video Experimental Relacionado

Updated: Sep 9, 2025

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics
10:52

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics

Published on: April 12, 2019

12.9K

Un algoritmo de predicción de la solubilidad en agua basado en el modelo StackBoost

Bin Pan1, Xiaoyu Hou1, Mingxin Zhang1

  • 1College of Science, LiaoNing Petrochemical University, Fushun, China.

PloS one
|August 29, 2025
PubMed
Resumen
Este resumen es generado por máquina.

Este estudio presenta StackBoost, un nuevo modelo para predecir la solubilidad en agua de los compuestos orgánicos. StackBoost supera significativamente a otros métodos de conjunto, ayudando a identificar compuestos con un alto potencial de solubilidad en agua.

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Área de la Ciencia:

  • Química computacional
  • Aprendizaje automático
  • Descubrimiento de drogas

Sus antecedentes:

  • La solubilidad en agua es una propiedad fisicoquímica crítica con amplias aplicaciones.
  • La determinación experimental de la solubilidad requiere muchos recursos.
  • La predicción precisa de la solubilidad es crucial para varios dominios científicos.

Objetivo del estudio:

  • Desarrollar y evaluar un nuevo modelo de aprendizaje conjunto, StackBoost, para predecir la solubilidad en agua de los compuestos orgánicos.
  • Comparar el rendimiento de StackBoost con los métodos de conjunto establecidos.
  • Evaluar la aplicabilidad del modelo en la detección de alto rendimiento y sus capacidades de generalización.

Principales métodos:

  • Desarrollo del modelo StackBoost.
  • Comparación sistemática con el impulso adaptativo (AdaBoost), los árboles de regresión impulsados por gradiente (GBRT), la máquina de impulso de gradiente ligero (LGBM), el impulso de gradiente extremo (XGBoost) y el bosque aleatorio (RF).
  • Validación mediante cribado de alto rendimiento en grandes conjuntos de datos y transferencia de aprendizaje.

Principales resultados:

  • StackBoost obtuvo un coeficiente de determinación (R2) de 0,90, un RMSE de 0,29 y un MAE de 0,22.
  • StackBoost superó significativamente a todos los modelos de conjunto comparativos.
  • El cribado de alto rendimiento identificó con éxito compuestos con alto potencial de solubilidad en agua.
  • El modelo demostró una considerable transferibilidad entre conjuntos de datos, lo que indica una buena capacidad de generalización.

Conclusiones:

  • StackBoost es un modelo muy eficaz para predecir la solubilidad en agua.
  • El modelo ofrece una alternativa eficiente en términos de recursos a los métodos experimentales.
  • StackBoost muestra una promesa para el cribado a gran escala y la predicción de solubilidad generalizable.