Mass spectrometry
Quantitative Evaluation of Hemp-Derived Vape Products for Accurate Labeling, Identification of Unknowns, and Stability
Non-Contact Detection of Fentanyl and Other Opioids: Towards a Generalized Approach to Detection of Dangerous Drug Classes
Research and Development for the Creation of Validated Protocols for the Forensic Detection and Quantification of Psilocybin and Psilocin in Complex Edible Matrices
Expert Algorithm to Identify Seized Drugs from Tandem Mass Spectra
On the reliability of the forensic examination of electrical tapes and the influence of alteration sources encountered in casework
Differentiation of Hemp and Marijuana Through Ion Complexation with Copper Phosphine Complexes
Semi-empirical Kinetics Model for Fingerprint Aging
Investigations Toward Development of a Technique for Rapid Identification of Forensically Relevant Necrophagous Beetle Species for Postmortem Interval Determination
A Combined Molecular Analysis of Pollen Utilizing Lipid Profiling & DNA Barcoding for Plant Species Identification: A Forensic Application
Advancing New Psychoactive Substance Detection by Performance Comparison of High-Resolution Mass Spectrometry Techniques
MDI Myth: Rapid Toxicology Screening Tools Can Replace Traditional Toxicology Testing – No Need to Confirm
Evaluating a Statistical Method for Comparison of Mass Spectra of Novel Psychoactive Substance
Quantitative Analysis Method for Tetrahydrocannabinol Isomers in Biological Matrices
Validation of a Confirmatory Proteomic Mass Spectrometry Body Fluid Assay
NIJ Announces $1.9M to Fund Research in Public Forensic Laboratories in 2023
On September 26, 2023, NIJ announced $1.9 million in funding to support five new projects under its Research and Evaluation for the Testing and Interpretation of Physical Evidence in Publicly Funded Forensic Laboratories (Public Labs R&E) program. Through its forensic science research funding, NIJ continues to improve the examination and interpretation of physical evidence across the community of practice through identification of the most efficient...