SolubilityModels 1.3.0

Tool for computational analysis of solubility models

Solubility Models Library

The analysis of multicomponent systems leads to elucidate or in its effect to describe in an approximate way the different phenomena as molecular interactions between the components of a system.

Understanding the behavior of these phenomena allows the development of theoretical models to predict the different properties of the system, generating computer tools that, in addition to facilitating the analysis, allow a better understanding of the different factors involved in the solution process.

One of the most important properties is the solubility, since it is one of the most important stages in the research and development of pharmaceutical products, since it affects the biopharmaceutical and pharmacokinetic characteristics of the pharmaceutical forms. It is, therefore, that one of the most important lines of research in solution thermodynamics are mathematical models that allow predicting solubility with very low error ranges.

Solubility Models

Solubility Models is a library for the calculation of fit parameters, calculated values, statisticians and plotting graph of calculated values and experimental of solubility models such as :

• Modified Apelblat

• van’t Hoff

• van’t Hoff-Yaws

• Modified Wilson

• Buchowski Ksiazaczak λh

• NRTL

• Wilson

• Weibull of two parameters

Installation of requirements

Before installing the library you must verify the execution environment and install the following requirements:

Google Colaboratory Support

For use in Google Colab (https://colab.research.google.com/) install texlive-fonts, texlive-fonts-extra and dvipng package using:

!apt install texlive-fonts-recommended texlive-fonts-extra cm-super dvipng

Jupyter Notebook and JupyterLab Support

For use in Jupyter Notebook and JupyterLab (https://anaconda.org/) install jupyter-dash and python-kaleido packages using:

conda install -c plotly jupyter-dash
conda install -c plotly python-kaleido

Datalore Support

For use in the enviroment Datalore (https://datalore.jetbrains.com) install texlive-fonts, texlive-fonts-extra and dvipng package using:

!sudo apt-get update
!sudo apt install texlive-fonts-recommended texlive-fonts-extra cm-super dvipng -y

Installation and import of SolubilityModels

Solubility models may be installed using pip…

!pip install SolubilityModels

To import all solubility models you can use:

from SolubilityModels.Models import *

To import a particular model you can use the model name e.g:

from SolubilityModels.Modified_Apelblat import *

Data Upload

For upload the dataset according to the format of the standard table (https://da.gd/CAx7m) as a path or url in extension “xlsx” or “csv” using:

data = dataset("url or path")

Class model

The model class allows the computational analysis of the data according to a particular solubility model, as an example, the following code is presented:

from SolubilityModels.Models import *
data = dataset("https://raw.githubusercontent.com/SolubilityGroup/Thermodynamic_Solutions/main/Test%20data/SMT-MeCN-MeOH.csv")

model_λh = model.buchowski_ksiazaczak(data,Tf = 471.55)

Equation method

Method to show the equation of the chosen solubility model.

model_λh.equation

Experimental values method

Method to show and download in different formats (“xlsx”,”csv”,”tex”,”pdf”) the dataframe experimental values of the model, the experimental mole fractions of solubility can be multiplied by a power of ten.

model_λh.experimental_values(scale = 2, download_format="tex")

Parameters method

Method to show the model fit parameters with their standard deviation for each mass fraction in a dataframe. Download in different formats the parameters dataframe.

model_λh.parameters(cmap ="Reds",download_format="tex")

Calculate values method

Method to show the table of calculated values of the solubility according to temperatures and mass fractions in a dataframe. Download in different formats the calculated values dataframe.

model_λh.calculated_values(scale=2,download_format="tex")

Relative deviations method

Method to show the table relative deviations for each value calculated according to temperatures and mass fractions in a dataframe. Download in different formats the relative deviations dataframe.

model_λh.relative_deviations(scale = 2,download_format="tex")

Statisticians method

Method to show the table of statisticians of the model in a dataframe

model_λh.statisticians(download_format="tex")

Plot method

Method to shows the graph of calculated values and experimental values of solubility completely or separately according to mass fractions. Download in different formats the graph.

model_λh.plot()

model_λh.plot(download_format="tex")

Contributors

• Prof. Jhonny Osorio Gallego, M.Sc.

https://github.com/josorio398

[e-mail]

• Prof. Rossember Eden Cárdenas Torres, M.Sc.

https://github.com/Rossember555

[e-mail]

• Ing. Cristhian David Rodriguez Quiroga

https://github.com/CQuiroga97

[e-mail]

• Prof. Claudia Patricia Ortiz, M.Sc.

https://github.com/cportiz/cportiz

[e-mail]

• Prof. Daniel Ricardo Delgado, Ph.D

https://github.com/drdelgad0

[e-mail]