A Digital Tool for Liquid-Liquid Extraction Process Design

13 March 2025, Version 1
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

Aqueous liquid-liquid extractions are crucial for purifying compounds and removing impurities in the pharmaceutical industry. However, the extensive solvent space involved in such operations highlights the need for an informed approach in solvent selection. We present a digital tool designed to leverage data-driven experimentation to enhance process efficiency and sustainability, aligning with industry trends towards digitalisation. It allows users to input various parameters, retrieve relevant data, and visualise extraction efficiencies, thereby improving process understanding and reducing process development lead times. By providing interactive visualisations and facilitating rapid hypothesis generation, the tool supports informed decision-making and streamlines workflows. The tool's application is demonstrated through representative complex scenarios involving the separation of compounds in a chemical reaction. Overall, this digital tool represents a significant advancement in chemical process design, promoting more sustainable and efficient practices in the industry.

Keywords

digitalisation
chemical processes
extraction

Supplementary materials

Title
Description
Actions
Title
Supplementary Information
Description
Supplementary Information
Actions
Title
pKa data
Description
Table of pKa data referenced in the main text and SI
Actions
Title
LogP data
Description
Table of LogP data referenced in the main text and SI
Actions
Title
SMILES
Description
Table of SMILES for compounds referenced in the main text and SI
Actions
Title
Solvents Physical Properties data
Description
Table of solvents with pysical properties data referenced in the main text and SI
Actions
Title
Python Code
Description
Standalone python code backend for the tool
Actions
Title
Code Example
Description
Jupyter Notebook demonstrating the use of the code to generate the results discussed in the main text.
Actions
Title
Results
Description
Table of results as obtained by running the provided code and discussed in the main text.
Actions

Comments

Comments are not moderated before they are posted, but they can be removed by the site moderators if they are found to be in contravention of our Commenting Policy [opens in a new tab] - please read this policy before you post. Comments should be used for scholarly discussion of the content in question. You can find more information about how to use the commenting feature here [opens in a new tab] .
This site is protected by reCAPTCHA and the Google Privacy Policy [opens in a new tab] and Terms of Service [opens in a new tab] apply.