Print Email Facebook Twitter Large sample neutron activation analysis avoids representative sub-sampling and sample preparation difficulties Title Large sample neutron activation analysis avoids representative sub-sampling and sample preparation difficulties: An added value for forensic analysis Author Bode, P. (TU Delft RST/Applied Radiation & Isotopes) Romanò, Sabrina (Sapienza University of Rome) Romolo, Francesco Saverio (Sapienza University of Rome) Date 2017-10 Abstract A crucial part of any chemical analysis is the degree of representativeness of the measurand(s) in the test portion for the same measurands in the object, originally collected for investigation. Such an object usually may have either to be homogenized and sub-sampled, or digested/dissolved. Any of these steps introduce sampling errors, risk of contamination or loss of the measurand(s). Neutron (and photon) activation analysis and prompt gamma analysis have the capabilities of analyzing large objects or samples without the need of any pre-treatment, i.e., intact 'as received', with masses varying from tens of grams to tens of kilograms, and with any type of (irregular) shape. The basic concept of neutron activation analysis and prompt gamma analysis are shortly revisited and the scope of application of the large sample analysis with these technique are elaborated on with an outlook for use in forensic studies, including the analysis of medicinal products and drugs of abuse. Subject Drugs of abuseHomogenizationLarge samplesMedicinal productsNeutron activation analysisPrompt gamma analysisRepresentativeness To reference this document use: http://resolver.tudelft.nl/uuid:993d93ff-366b-4089-ba14-ba6682584b3e DOI https://doi.org/10.1016/j.forc.2017.10.002 Embargo date 2019-10-13 ISSN 2468-1709 Source Forensic Chemistry, 1-7 Part of collection Institutional Repository Document type journal article Rights © 2017 P. Bode, Sabrina Romanò, Francesco Saverio Romolo Files PDF Full_paper_Bode_LSNAA_for ... evised.pdf 785 KB Close viewer /islandora/object/uuid:993d93ff-366b-4089-ba14-ba6682584b3e/datastream/OBJ/view