Infrared spectroscopy-assisted prediction of impurities in chemicals using machine learning: towards smart self-driving laboratories
Abstract
-score of 0.99 for functional group determination was achieved for the real spectra and 0.95 for the purity determination task was observed. In fact, the model was able to determine whether a compound was pure enough for further use or contaminated with the identified substance and should be purified.
Fields of Study & Subjects
Machine Learning in Materials Science
Spectroscopy and Chemometric Analyses
Spectroscopy and Laser Applications
Publication details
- Journal / source
- Physical Chemistry Chemical Physics
- Volume
- 28
- Issue
- 6
- Pages
- 3939–3948
- Publication date
- 1 January 2026
- Language
- EN