Classic inorganic gunshot residue analysis (IGSR) relies on standardized protocols that offer confidence to practitioners when conducting these examinations. However, the evolution of ammunition to greener alternatives and technological advances are changing the identification and interpretation paradigms. Organizations like NIST/OSAC and NIJ/TWG have reported relevant gaps in this field. For instance, the development of technologies that offer extended detection to include non-traditional organic markers (OGSR). Also, access to reference materials can lead to harmonized QC policies across laboratories. Finally, there is a demand for interpretation models that incorporate analytical data, collection, deposition, and persistence information to assess the weight of the evidence. This study aims to address those priorities by developing solutions that increase the reliability and efficiency of GSR examinations.
The overarching goal of this study was to build capacity with emerging methods and standard materials and increase the quality and usage of data. This was accomplished through four specific goals. First, to design characterized organic and inorganic GSR reference standards representative of modern ammunition for research and crime laboratories. This tailor-made standard was created for QC, validation of existing and new methods, and interlaboratory testing. Second, to develop novel routes for studying the transfer and persistence of IGSR and OGSR using our tailor-made standard. To this end, a known number of characterized GSR particles were deposited on over 600 specimens under systematic and controlled conditions to evaluate different factors that affect GSR retention (e.g., activities, time, ammunition, and clothing types).
Third, to compare the performance and cost-efficiency of portable and bench-top LIBS and electrochemical systems, using over 1000 authentic GSR samples and standards, through a strategic collaboration with industry and practitioners. The portable instrumentation expands the utility of the methods to an on-site testing platform currently unavailable in the field while potentially transforming case management and decision-making processes. Finally, this study applied statistical methods for interpreting GSR evidence considering probabilistic approaches and Bayesian networks, using the data from an extensive population database. This work addressed several needs in the field and responded to more than one of the national priorities identified by NIJ: a) educating and training a future workforce, b) transferring technology from laboratory to marketplace, and c) partnering with industry and academia. The findings of this study provide a robust platform for training the next generation of forensic scientists and for future applications to the collection, examination, and interpretation of evidence in the criminal justice system.
(Author abstract provided.)
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