Automated synthesis and fragment descriptor-based machine learning for retention time prediction in supercritical fluid chromatography

2025/11/26 by Sitanan Sartyoungkul, Balasubramaniyan Sakthivel, Pavel Sidorov +1 · 1 voice
Chemistry · Engineering · #Analytical Chemistry and Chromatography #Chromatography in Natural Products #Phase Equilibria and Thermodynamics

paper · pdf · doi:10.1039/d5dd00437c

openalex publication_date 2025/11/26 · openalex created_date 2025/11/27 · openalex updated_date 2026/06/11

Abstract

Integration of automated synthesis and fragment descriptor-based machine learning enables accurate prediction of SFC retention times and accelerates column characterization.

Citations

• DOPtools: a Python platform for descriptor calculation and model optimization

Discussions

• 🖥️ Yuuya Nagata and his team combine automated synthesis and machine learning models in their new #DigitalDiscovery manuscript which works to transform chromatographic workflows through a new model r [bsky, 0 points, 0 comments]

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