{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["10(1)"],"submitter":["Hammer P"],"pubmed_abstract":["The analysis of thermal desorption spectra (TDS) and the calculation of hydrogen detrapping activation energies rely on Gaussian peak deconvolution and Choo-Lee plot regression since 1982. However, this method imposes important assumptions about the number and shape of the TDS peaks used for fitting. In this study, we propose the <i>fingerprint</i> method, an alternative approach that eliminates these long-standing constraints. By applying the <i>fingerprint</i> analysis to eight TDS spectra from three different Fe-C model alloys, we demonstrate its exceptional sensitivity and ability to resolve activation energy distributions - the material <i>fingerprint</i> - unattainable with traditional methods. We further showcase by manual and automated analysis how the such obtained <i>fingerprints</i> can be used to uniquely distinguish the TDS spectra of each alloy independent of the heating rate. Thus the <i>fingerprint</i> method also increases experimental efficiency by reducing the amount of necessary heating rates for TDS down to one."],"journal":["Npj Materials degradation"],"pagination":["7"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12799485"],"repository":["biostudies-literature"],"pubmed_title":["The fingerprint method for analysis of thermal desorption spectra."],"pmcid":["PMC12799485"],"pubmed_authors":["Depover T","Vandewalle L","Hammer P","Verbeken K","Peil OE","Razumovskiy VI","Azizpour A"],"additional_accession":[]},"is_claimable":false,"name":"The fingerprint method for analysis of thermal desorption spectra.","description":"The analysis of thermal desorption spectra (TDS) and the calculation of hydrogen detrapping activation energies rely on Gaussian peak deconvolution and Choo-Lee plot regression since 1982. However, this method imposes important assumptions about the number and shape of the TDS peaks used for fitting. In this study, we propose the <i>fingerprint</i> method, an alternative approach that eliminates these long-standing constraints. By applying the <i>fingerprint</i> analysis to eight TDS spectra from three different Fe-C model alloys, we demonstrate its exceptional sensitivity and ability to resolve activation energy distributions - the material <i>fingerprint</i> - unattainable with traditional methods. We further showcase by manual and automated analysis how the such obtained <i>fingerprints</i> can be used to uniquely distinguish the TDS spectra of each alloy independent of the heating rate. Thus the <i>fingerprint</i> method also increases experimental efficiency by reducing the amount of necessary heating rates for TDS down to one.","dates":{"release":"2026-01-01T00:00:00Z","publication":"2026","modification":"2026-06-11T05:20:52.28Z","creation":"2026-06-11T03:08:03.343Z"},"accession":"S-EPMC12799485","cross_references":{"pubmed":["41540998"],"doi":["10.1038/s41529-025-00718-z"]}}