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Automated solubility screening platform using computer vision
- Source :
- iScience, iScience, Vol 24, Iss 3, Pp 102176-(2021)
- Publication Year :
- 2021
- Publisher :
- Elsevier, 2021.
-
Abstract
- Summary Solubility screening is an essential, routine process that is often labor intensive. Robotic platforms have been developed to automate some aspects of the manual labor involved. However, many of the existing systems rely on traditional analytic techniques such as high-performance liquid chromatography, which require pre-calibration for each compound and can be resource consuming. In addition, automation is not typically end-to-end, requiring user intervention to move vials, establish analytical methods for each compound and interpret the raw data. We developed a closed-loop, flexible robotic system with integrated solid and liquid dosing capabilities that relies on computer vision and iterative feedback to successfully measure caffeine solubility in multiple solvents. After initial researcher input (<br />Graphical abstract<br />Highlights • We demonstrate a modular, closed-loop robotic platform for solubility screening • Automated solvent titration is informed by computer vision and turbidity monitoring • No human intervention or HPLC analysis is required during the experimental loop • Solubility values obtained by the system match those obtained via traditional methods<br />Organic chemistry; organic synthesis; green chemistry; engineering; automation
- Subjects :
- 0301 basic medicine
Computer science
Process (engineering)
engineering
02 engineering and technology
010402 general chemistry
01 natural sciences
Article
03 medical and health sciences
Resource (project management)
Computer vision
Solubility
lcsh:Science
automation
Solvent system
Measure (data warehouse)
Multidisciplinary
010405 organic chemistry
business.industry
green chemistry
021001 nanoscience & nanotechnology
organic synthesis
Automation
0104 chemical sciences
organic chemistry
030104 developmental biology
Robotic systems
lcsh:Q
Artificial intelligence
0210 nano-technology
business
Raw data
Subjects
Details
- Language :
- English
- ISSN :
- 25890042
- Volume :
- 24
- Issue :
- 3
- Database :
- OpenAIRE
- Journal :
- iScience
- Accession number :
- edsair.doi.dedup.....4607408bd67babc27d75c31f8424d1c2