LSS and QSRR combined modelling for mechanistic elucidation of phenolic compound retention under diverse reversed-phase conditions

This study shows how combining LSS with QSRR offers a dual advantage of predictive performance and mechanistic interpretation for reversed-phase HPLC of phenolic compounds. By quantitatively linking molecular properties to chromatographic retention across diverse column and solvent conditions, the approach enhances understanding of key interactions governing separation. The resulting framework provides a practical tool for improving method development, particularly in complex phenolic mixtures and high-throughput analytical workflows.