Retention Index

Retention index (RI) is a crucial metric in analytical chemistry, particularly in chromatography, used to identify and characterize chemical compounds based on their elution time relative to known standards. Current research focuses on improving RI prediction accuracy using machine learning, employing techniques like deep neural networks and graph neural networks to model the relationship between molecular structure and RI, often incorporating ensemble methods for uncertainty quantification. These advancements enhance chemical identification, streamline experimental workflows, and improve the quality of spectral libraries, ultimately accelerating scientific discovery and impacting various fields relying on chemical analysis.