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相关概念视频

Entropy and Solvation02:05

Entropy and Solvation

7.1K
The process of surrounding a solute with solvent is called solvation. It involves evenly distributing the solute within the solvent. The rule of thumb for determining a solvent for a given compound is that like dissolves like. A good solvent has molecular characteristics similar to those of the compound to be dissolved. For example, polar solutions dissolve polar solutes, and apolar solvents dissolve apolar solutes. A polar solvent is a solvent that has a high dielectric constant (ϵ...
7.1K
Chemical and Solubility Equilibria02:21

Chemical and Solubility Equilibria

4.1K
The free energy change associated with dissolving a solute in a liter of solvent is called the free energy of a solution, ΔGsolution. The overall ΔGsolution is expressed as the balance of ΔGinteraction against the always-favorable free-energy of mixing, ΔGmixing. Solution formation is favorable if  ΔGsolution is less than zero, whereas it is unfavorable if ΔGsolution is greater than zero. In short, for a solution to form and complete dissolution to take place,...
4.1K
Enthalpy of Solution02:39

Enthalpy of Solution

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There are two criteria that favor, but do not guarantee, the spontaneous formation of a solution:
24.9K
Predicting Molecular Geometry02:27

Predicting Molecular Geometry

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VSEPR Theory for Determination of Electron Pair Geometries
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Gibbs Free Energy02:39

Gibbs Free Energy

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One of the challenges of using the second law of thermodynamics to determine if a process is spontaneous is that it requires measurements of the entropy change for the system and the entropy change for the surroundings. An alternative approach involving a new thermodynamic property defined in terms of system properties only was introduced in the late nineteenth century by American mathematician Josiah Willard Gibbs. This new property is called the Gibbs free energy (G) (or simply the free...
33.6K
Solubility Equilibria03:07

Solubility Equilibria

52.8K
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...
52.8K

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Unraveling Entropic Rate Acceleration Induced by Solvent Dynamics in Membrane Enzymes
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可解释的监督机器学习模型来预测溶解 吉布斯能量

José Ferraz-Caetano1, Filipe Teixeira2, M Natália D S Cordeiro1

  • 1Department of Chemistry and Biochemistry - Faculty of Sciences, University of Porto - Rua do Campo Alegre, S/N, 4169-007 Porto, Portugal.

Journal of chemical information and modeling
|August 21, 2023
PubMed
概括

我们开发了一种新的机器学习模型,以高准确性和速度预测溶解自由能量 (ΔGsol). 这种模型提供了宝贵的化学见解,在不需要复杂的模拟的情况下,其性能优于现有的方法.

科学领域:

  • 计算化学计算化学
  • 机器学习应用 机器学习应用

背景情况:

  • 准确预测溶解自由能量 (ΔGsol) 仍然是计算模型面临的挑战.
  • 现有的机器学习 (ML) 方法提供了速度,但缺乏广泛的化学预测的解释能力.

研究的目的:

  • 开发一种新的监督ML模型,用于预测ΔGsol.
  • 为了实现一个有利的速度-准确性权衡与增强的解释性见解.

主要方法:

  • 在ML模型开发中使用了两个集合回归算法.
  • 采用开源化学特征编码电子,结构和表面积描述符.
  • 综合分子特性和化学相互作用特征用于分析.

主要成果:

  • 在 ΔGsol 预测中实现了高精度,超过了基准神经网络方法.
  • 确定了极地表面积的增加和极化能力的减少作为主要的溶液描述符.
  • 证明最大绝对误差为0.22 ± 0.02 kcalmol-1.1,其中最大的绝对误差为0.22 ± 0.02 kcal.
  • 在外部数据库和通过溶剂保留试验验证实模型性能.

结论:

  • 开发的ML模型提供了一个快速而准确的方法来预测ΔGsol.

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  • 该模型为描述符的重要性提供了有价值的解释性见解.
  • 这种方法有可能预测计算化学中的其他热力学性质.