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相关概念视频

Thermodynamics: Activity Coefficient01:24

Thermodynamics: Activity Coefficient

1.3K
Activity is the measure of the effective concentration of the species in solution. It can be expressed as the product of the molar concentration of the species and its activity coefficient. The activity coefficient is a dimensionless quantity and depends on the total ionic strength of the solution.
The activity coefficient is a measure of the deviation from ideal behavior. When the ionic strength of the solution is minimal, the activity coefficient of an ionic species is close to unity, making...
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Factors Affecting Activity Coefficient01:17

Factors Affecting Activity Coefficient

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The extended Debye-Hückel equation indicates that the activity coefficient of an ion in an aqueous solution at 25°C depends on three partially interdependent properties: the ionic strength of the solution, the charge of the ion, and the ion size. 
The activity coefficient value for an ion is close to one when the solution has almost zero ionic strength, i.e., when the solution shows close to ideal behavior. As the ionic strength of the solution increases from 0 to 0.1 mol/L, a...
753
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

41
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
41
Chemical Equilibria: Redefining Equilibrium Constant01:20

Chemical Equilibria: Redefining Equilibrium Constant

540
The effect of an inert salt on the solubility of a sparingly soluble salt is known as the salt effect. The degree of the salt effect varies with the ionic strength of the solution, which in turn depends on the activity of the species in the solution. The activity is expressed as the product of concentration and the activity coefficient of the species.
To calculate the equilibrium constants of solutions of moderately high ionic strength, one must account for the salt effect. This redefined...
540
Determining the pH of Salt Solutions04:08

Determining the pH of Salt Solutions

43.3K
The pH of a salt solution is determined by its component anions and cations. Salts that contain pH-neutral anions and the hydronium ion-producing cations form a solution with a pH less than 7. For example, in ammonium nitrate (NH4NO3) solution, NO3− ions do not react with water whereas NH4+ ions produce the hydronium ions resulting in the acidic solution.  In contrast, salts that contain pH-neutral cations and the hydroxide ion-producing anions form a solution with a pH greater than...
43.3K
Calculating Equilibrium Concentrations02:05

Calculating Equilibrium Concentrations

47.5K
Being able to calculate equilibrium concentrations is essential to many areas of science and technology—for example, in the formulation and dosing of pharmaceutical products. After a drug is ingested or injected, it is typically involved in several chemical equilibria that affect its ultimate concentration in the body system of interest. Knowledge of the quantitative aspects of these equilibria is required to compute a dosage amount that will solicit the desired therapeutic effect.
A more...
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根据机器学习算法快速计算NaCl溶液的活性系数.

Bowen Qin1,2, Yizhong Zhang1,2, Long Yang3

  • 1School of Petroleum Engineering, Yangtze University, Wuhan City 430100, China.

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概括

机器学习快速计算二氧化碳储存模拟活动系数. 这种方法将计算速度提高48%,并使用温度和压力来确定地质化学建模的Debye-Hückel参数.

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科学领域:

  • 地质化学 地质化学
  • 计算化学的计算化学
  • 机器学习应用 机器学习应用

背景情况:

  • 活动系数量化了与理想溶液的偏差,影响了二氧化碳在盐水中的溶解度和扩散,这对地质储存至关重要.
  • 当前的数值模拟通常使用Helgeson-Kirkham-Flowers (HKF) 方程,需要通过缓慢的插值算法计算Debye-Hückel (DH) 参数.
  • 有效计算活动系数对于优化二氧化碳地质储存模拟至关重要.

研究的目的:

  • 开发一种更快,更准确的方法来计算地化学反应建模中的活性系数.
  • 使用基于温度和压力的机器学习来建立Debye-Hückel (DH) 参数的经验公式.
  • 将这些经验公式集成到Helgeson-Kirkham-Flowers (HKF) 方程中,以便快速计算活动系数.

主要方法:

  • 机器学习算法在Debye-Hückel (DH) 参数上进行训练,这些参数来自IAPWS-95方法.
  • 建立了经验公式来表达DH参数作为温度和压力的函数.
  • 这些公式被替换到HKF方程中来计算活动系数.

主要成果:

  • 机器学习方法产生了活动系数,与实验值相对偏差很小 (平均R2为0.9463,平均相对误差为2.28%).
  • 活动系数计算的计算速度提高了48%.
  • 该方法允许仅根据温度和压力在广泛范围内 (0300°C,0200MPa) 计算DH参数.

结论:

  • 这项研究提出了一种高精度和高效的方法来计算活动系数,大大减少了地质化学模拟中的计算时间.
  • 开发的经验公式使得DH参数的快速确定成为可能,从而促进了精确的二氧化碳储存建模.
  • 这种方法对于在深海盐水中推进地化学反应的数值模拟至关重要.