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