Print Email Facebook Twitter Large area imaging of forensic evidence with MA-XRF Title Large area imaging of forensic evidence with MA-XRF Author Langstraat, Kirsten (Netherlands Forensic Institute - NFI) Knijnenberg, Alwin (Netherlands Forensic Institute - NFI) Edelman, Gerda (Netherlands Forensic Institute - NFI) Van De Merwe, Linda (Netherlands Forensic Institute - NFI) van Loon, A. (TU Delft (OLD) MSE-4; Rijksmuseum) Dik, J. (TU Delft (OLD) MSE-4) van Asten, Arian C. (Netherlands Forensic Institute - NFI; Universiteit van Amsterdam; CLHC) Date 2017 Abstract This study introduces the use of macroscopic X-ray fluorescence (MA-XRF) for the detection, classification and imaging of forensic traces over large object areas such as entire pieces of clothing and wall paneling. MA-XRF was sufficiently sensitive and selective to detect human biological traces like blood, semen, saliva, sweat and urine on fabric on the basis of Fe, Zn, K, Cl and Ca elemental signatures. With MA-XRF a new chemical contrast is introduced for human stain detection and this can provide a valuable alternative when the evidence item is challenging for conventional techniques. MA-XRF was also successfully employed for the chemical imaging and classification of gunshot residues (GSR). The full and non-invasive elemental mapping (Pb, Ba, Sr, K and Cl) of intact pieces of clothing allows for a detailed shooting incident reconstruction linking firearms and ammunition to point of impact and providing information on the shooting angle. In high resolution mode MA-XRF can even be used to provide information on the shooting order of different ammunition types. Finally, by using the surface penetration of X-rays we demonstrate that the lead signature of a bullet impact can be easily detected even if covered by multiple layers of wall paint or human blood. Subject DNAImaging studies To reference this document use: http://resolver.tudelft.nl/uuid:bac5be1c-ed96-4dea-88da-a7460ab21ed5 DOI https://doi.org/10.1038/s41598-017-15468-5 ISSN 2045-2322 Source Scientific Reports, 7 (1) Part of collection Institutional Repository Document type journal article Rights © 2017 Kirsten Langstraat, Alwin Knijnenberg, Gerda Edelman, Linda Van De Merwe, A. van Loon, J. Dik, Arian C. van Asten Files PDF s41598_017_15468_5.pdf 4.11 MB Close viewer /islandora/object/uuid:bac5be1c-ed96-4dea-88da-a7460ab21ed5/datastream/OBJ/view