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Enhanced accuracy through machine learning-based simultaneous evaluation: a case study of RBS analysis of multinary materials

 
dc.contributor.authorMagchiels, Goele
dc.contributor.authorClaessens, Niels
dc.contributor.authorMeersschaut, Johan
dc.contributor.authorVantomme, Andre
dc.contributor.imecauthorClaessens, Niels
dc.contributor.imecauthorMeersschaut, Johan
dc.contributor.orcidimecClaessens, Niels::0000-0002-8863-9532
dc.contributor.orcidimecMeersschaut, Johan::0000-0003-2467-1784
dc.date.accessioned2024-11-18T11:08:42Z
dc.date.available2024-05-02T17:47:54Z
dc.date.available2024-11-18T11:08:42Z
dc.date.embargo2024-04-08
dc.date.issued2024
dc.description.wosFundingTextThis work was supported by FWO (Research Foundation Flanders) and the EU infrastructure network RADIATE (grant agreement 824096). The authors thank Jelle Demeulemeester for the collection and human supervision analysis of the experimental data set.
dc.identifier.doi10.1038/s41598-024-58265-7
dc.identifier.issn2045-2322
dc.identifier.pmidMEDLINE:38589457
dc.identifier.urihttps://imec-publications.be/handle/20.500.12860/43894
dc.publisherNATURE PORTFOLIO
dc.source.beginpageArt. 8186
dc.source.endpageN/A
dc.source.issue1
dc.source.journalSCIENTIFIC REPORTS
dc.source.numberofpages11
dc.source.volume14
dc.subject.keywordsION-BEAM ANALYSIS
dc.title

Enhanced accuracy through machine learning-based simultaneous evaluation: a case study of RBS analysis of multinary materials

dc.typeJournal article
dspace.entity.typePublication
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