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1.
J Forensic Sci ; 67(2): 505-515, 2022 Mar.
Article in English | MEDLINE | ID: mdl-34799855

ABSTRACT

Aluminum (Al) powder is commonly encountered in improvised explosive devices (IEDs) as a metallic fuel due to its availability and low cost. Although available commercially in powder form, amateur bomb-makers also produce their own Al powder via simple methods found online. In order to provide investigative leads and forensic intelligence, it is important to evaluate not only the composition of homemade devices, but also to distinguish between the various forms of Al powder they contain. To achieve this goal, a method using automated microscopy in combination with statistical techniques has been demonstrated to have the potential to provide source discrimination and investigative leads in source attribution of Al powders in IEDs. The present research refined this method and investigated 59 industrially and amateurly produced Al powder sources with seven subsamples per source using two traditional linear discriminant analyses (LDA), one with a standard data split for training and testing, and another using leave-one-out cross-validation. Averaging the classification accuracies for the two LDA-based analyses, LDA has the ability to correctly classify 59.26%, 83.35%, and 80.69% of the samples based on their powder source, type, and production method, respectively. This classification accuracy represents a 3407%, 317%, and 61.38% increase in accuracy from random class assignment, respectively. Further, in most instances of incorrect data attribution to a particular source, the subsample has been misidentified with another sample of the same powder type or production method.

2.
J Forensic Sci ; 66(1): 83-95, 2021 Jan.
Article in English | MEDLINE | ID: mdl-33006770

ABSTRACT

Aluminum (Al) powders are commonly used in improvised explosive devices as metallic fuels, a component of explosive mixtures. These powders can be obtained readily from industrial-scale and consumer products, and produced using unsophisticated "kitchen chemistry" techniques. This research demonstrates the potential of automated particle micromorphometry for comparisons between known source and questioned Al powders recovered from IEDs, as well as for insight into the method of Al powder manufacture. Al powder samples were obtained from legitimate manufacturers, and 56 samples were produced "in-house" from Al-containing spray paints and ball-milled Al foils. Transmitted light microscope images of Al powder particles were acquired using an automated stage with automated z-focus; 17 size and shape parameters were measured for all particles. Approximately 37,000-2,500,000 particles/sample were analyzed using an open-source statistical package with customized code. Dimensionality reduction was required for processing the large datasets: eight of the 17 measured variables were selected based on inspection of the correlation matrix. Data from four subsamples from each of the 56 samples produced using "in-house" methods were analyzed using ANOVA to assess the within- and between-sample variation. High within-sample variation was noted; however, ANOVA and post-hoc Tukey's honestly significant difference (HSD) tests demonstrated that the between-sample variation was substantially larger than the within-sample variation. Each sample could be differentiated from all other samples in the test set. Future experiments will focus on ways to reduce the within-sample variation, and additional statistical and microanalytical methods to classify sources and confidently constrain the method of Al powder manufacture.

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