Automated synthesis and fragment descriptor-based machine learning for retention time prediction in supercritical fluid chromatography
Integration of automated synthesis and fragment descriptor-based machine learning enables accurate prediction of SFC retention times and accelerates column characterization.
Authors
- Sitanan Sartyoungkul (ORCID: https://orcid.org/0000-0001-5771-538X)
- Pavel Sidorov (ORCID: https://orcid.org/0000-0001-6462-702X)
- S. Balasubramaniyan (ORCID: https://orcid.org/0000-0003-1066-9878)
- Yuuya Nagata
Institutions
- Hokkaido University (JP)
- National Institute for Materials Science (JP)
Publication Details
- Journal
- Digital Discovery
- Published
- 2025-11-26
- DOI
- https://doi.org/10.1039/d5dd00437c
- Primary Topic
- Analytical Chemistry and Chromatography
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Ministry of Education, Culture, Sports, Science and Technology
- Japan Society for the Promotion of Science
- Exploratory Research for Advanced Technology