Liquid chromatography–mass spectrometry (LC–MS)-based untargeted metabolomics is
constantly challenged by large-scale and unambiguous metabolite annotation in complex …

Advances in chromatographic technology depend to a large extent on the development of
novel stationary phases with enhanced separation efficiency to meet the ever-growing …

There is an increasing need for comparable and harmonized retention times (t R) in liquid
chromatography (LC) among different laboratories, to provide supplementary evidence for …

Food fraud is currently a growing global concern with far‐reaching consequences. Food
authenticity attributes, including biological identity, geographical origin, agricultural …

The demand for rapid column screening, computer-assisted method development and
method transfer, and unambiguous compound identification by LC/MS analyses has pushed …

Retention time prediction in high-performance liquid chromatography (HPLC) is the subject
of many studies since it can improve the identification of unknown molecules in untargeted …

In metabolomics, retention prediction methods have been developed based on the structural
and physicochemical characteristics of analytes. Such methods employ regression models …

Non-target analysis (NTA) employing high-resolution mass spectrometry (HRMS) coupled
with liquid chromatography is increasingly being used to identify chemicals of biological …

Many organic chemicals are present in aquatic environments, but how to screen and
prioritize these chemicals has always been a difficult task. Here we investigated organic …

Retention time prediction, facilitated by advances in machine learning, has become a useful
tool in untargeted LC-MS applications. State-of-the-art approaches include graph neural …