Abstract
A searchable printing ink database was designed and validated as a tool to improve the chemical information gathered from the analysis of ink evidence. The database contains 319 samples from printing sources that represent some of the global diversity in toner, inkjet, offset, and intaglio inks. Five analytical methods were used to generate data to populate the searchable database including FTIR, SEM-EDS, LA-ICP-MS, DART-MS, and Py-GC-MS. The search algorithm based on partial least-squares discriminant analysis generates a similarity "score" used for the association between similar samples. The performance of a particular analytical method to associate similar inks was found to be dependent on the ink type with LA-ICP-MS performing best, followed by SEM-EDS and DART-MS methods, while FTIR and Py-GC-MS were less useful in association but were still useful for classification purposes. Data fusion of data collected from two complementary methods (i.e., LA-ICP-MS and DART-MS) improves the classification and association of similar inks.
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