This study presents a forensic approach to classify temporal evolution stages and predict the aging time of gel-pen ink using Gas Chromatography–Ion Mobility Spectrometry (GC-IMS) combined with machine learning algorithms. The method enables precise ink dating, enhancing document authentication and forgery detection.
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