Prediction of Collision Cross-Section Values for Extractables and Leachables from Plastic Products
Xue‐Chao Song, Nicola Dreolin, Elena Canellas, Jeff Goshawk, Cristina Nerı́n
Abstract
adducts were 1.42 and 1.76%, respectively. Subsequently, CCS values for the compounds in the Chemicals associated with Plastic Packaging Database and the Food Contact Chemicals Database were predicted using the SVM model developed herein. These values were integrated in our structural elucidation workflow and applied to the identification of plastic-related chemicals in river water. False positives were reduced, and the identification confidence level was improved by the incorporation of predicted CCS values in the suspect screening workflow.
Topics & Concepts
Support vector machineIdentification (biology)False positive paradoxChemistryIon-mobility spectrometryMolecular descriptorWorkflowCollisionMass spectrometryComputer scienceMachine learningChromatographyDatabaseQuantitative structure–activity relationshipComputer securityBiologyBotanyMicroplastics and Plastic PollutionEffects and risks of endocrine disrupting chemicalsAdvanced Chemical Sensor Technologies