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Determining Phase Separation Dynamics with an Automated Image Processing Algorithm

delete2023-03-14
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OA
AI
J
James Daglish
A
A. John Blacker
G
Gregory de Boer
A
Alex Crampton
D
David R. J. Hose
A
Anna R. Parsons
N
Nikil Kapur *
DOI:10.1021/acs.oprd.2c00357delete
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Abstract

Abstract

En 中文
The problems of extracting products efficiently from reaction workups are often overlooked. Issues such as emulsions and rag layer formation can cause long separation times and slow production, thus resulting in manufacturing inefficiencies. To better understand science within this area and to support process development, an image processing methodology has been developed that can automatically track the interface between liquid-liquid phases and provide a quantitative measure of the separation rate of two immiscible liquids. The algorithm is automated and has been successfully applied to 29 cases. Its robustness has been demonstrated with a variety of different liquid mixtures that exhibit a wide range of separation behavior-making such an algorithm suited to high-throughput experimentation. The information gathered from applying the algorithm shows how issues resulting from poor separations can be detected early in process development.
Keywords:
separation science
image analyses
emulsion
liquid-liquid system
AI Summary

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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

O
Organic Process Research and Development
IF:
3.5
Papers:
5.8K
Citations:
1.1W

Organization

A
AstraZeneca
Scholars:
2.1W
Papers: 1.1W
Citations: 36
U
university of leeds
Scholars:
3.6W
Papers: 3.3W
Citations: 45
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