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Investigation of volatile organic compounds from trace fentanyl powder via passive degradation

NCJ Number
Forensic Chemistry Volume: 31 Dated: December 2022
Date Published
December 2022

This article presents research into the development of a non-contact method for the detection of synthetic opioids, specifically fentanyl.


Deaths as a result of overdose are increasing exponentially due to the frequent incorporation of synthetic opioids such as fentanyl with other traditional illicit drugs. Low amounts of fentanyl, as little as 2 mg, are sufficient to cause an overdose, making it 50 times more potent than heroin. Non-contact detection methods provide a valuable tool for law enforcement that will increase safety for first responders who may come into contact with this harmful substance. Previously published reports have stated that fentanyl undergoes degradation under intense oxidative and irradiated environments. However, there is no evidence of how fentanyl is affected by passive environments. Additionally, a greater understanding of the fentanyl headspace as it degrades will provide a more concise identification of fentanyl by non-contact vapor detection methods. The vapor signature of fentanyl as it is stored over time is discussed herein. Free-base fentanyl was placed in various environments to mimic the storage of clandestine manufacturing. Eight environments and two storage containments were studied by manipulating heat, humidity and oxygen levels. Headspace samples were collected via Solid Phase Microextraction (SPME) and analyzed via GC–MS. A total of nine VOCs were identified throughout the study, overall, N-phenylpropanamide (NPPA) and styrene were identified as the most abundant degradative components within the fentanyl headspace. Further investigation on the effects of plastic and tape wrappings on the fentanyl headspace as it degrades did not interfere with the detected NPPA as it remained the most abundant degradant. Results of this study will enable the development of non-contact vapor detection methods. (Published Abstract Provided)

Date Published: December 1, 2022