Research output per year
Research output per year
Ruben F. Kranenburg*, Yannick Weesepoel, Martin Alewijn, Sharon Sap, Peter W.F. Arisz, Annette van Esch, Peter H.J. Keizers, Arian C. van Asten
Research output: Contribution to journal › Article › Academic › peer-review
Both the increasing volume and diversity of drugs-of-abuse encountered by investigation services necessitates the need for fast on-scene detectors to detect and identify a broad range of substances. Near-Infrared (NIR) spectroscopy is suitable for presumptive drugs testing by miniaturized sensors implemented in portable devices. Currently, a myriad of different portable NIR spectrometers is available that utilize different wavelength ranges. This study presents a comparison of NIR spectra of frequently occuring drugs analyzed by five different devices. A 350 – 2500 nm range laboratory grade VIS-NIR spectrometer was used to gain insight in spectral ranges diagnostic for substances relevant in forensic science. Obtained spectra were compared to the output of portable spectrometers operating in the 740 – 1070 nm, 950 – 1650 nm, 1550 – 1950 nm and 1300 – 2600 nm range. The results yielded novel insights in the usability of individual spectrometers by visual inspection of NIR spectra as well as comparative statistics with reference substances. For MDMA detection, an instrument capable of detecting a highly abundant and specific peak at 2020 nm is beneficial whereas colored samples are more difficult to detect by lower wavelength range sensors. Relatively pure, lightly colored samples may be correctly characterized by all sensors. These findings may aid NIR spectrometer selection in forensic practice as well as future studies on instrument selectivity or cross-platform calibration transfer.
Original language | English |
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Article number | 100437 |
Journal | Forensic Chemistry |
Volume | 30 |
DOIs | |
Publication status | Published - Sept 2022 |
Research output: Contribution to journal › Article › Academic › peer-review
Kranenburg, R. F. (Creator), Weesepoel, Y. (Creator), Alewijn, M. (Creator), Sap, S. (Creator), Arisz, P. W. F. (Creator), van Esch, A. (Creator), Keizers, P. H. J. (Creator) & van Asten, A. C. (Creator), University of Amsterdam, 30 Sept 2022
Dataset