-
Categories
-
Pharmaceutical Intermediates
-
Active Pharmaceutical Ingredients
-
Food Additives
- Industrial Coatings
- Agrochemicals
- Dyes and Pigments
- Surfactant
- Flavors and Fragrances
- Chemical Reagents
- Catalyst and Auxiliary
- Natural Products
- Inorganic Chemistry
-
Organic Chemistry
-
Biochemical Engineering
- Analytical Chemistry
-
Cosmetic Ingredient
- Water Treatment Chemical
-
Pharmaceutical Intermediates
Promotion
ECHEMI Mall
Wholesale
Weekly Price
Exhibition
News
-
Trade Service
Thin layer chromatography (TLC) is widely used in synthetic chemistry laboratories and is one of the most commonly used analytical methods for the monitoring of organic reactions as well as for determining the location
Mo Fanyang's research group of the School of Materials Science and Engineering built a robot platform, developed the automation technology of TLC analysis, obtained a large amount of standardized TLC data, and then applied machine learning to regression analysis of the data to obtain a model
Automation and machine learning are combined to establish TLC predictive models
The researchers used MACCSKey molecular fingerprints and physicochemical descriptors, such as molecular weight (MW), topological polarity surface area (TPSA), and hydrogen bond donor number (HBD), to convert molecules into numerical structures that computers can process; Weighted vector coding is used to represent mobile phase information
Feature engineering and model prediction accuracy
The researchers assessed the relative importance
The relevant research results were published in Chem (Doi:10.
Related video links:
Links:
https://doi.
