Linking ammonium nitrate-aluminum (AN-AL) post-blast residues to pre-blast explosive materials using isotope ratio and trace elemental analysis for source attribution.

Forensic science practitioners are often called upon to attribute crimes using trace evidence, such as explosive remnants, with the ultimate goal of associating a crime with a suspect or suspects in order to prevent further attacks. The explosive charge is an attractive component for attribution in crimes involving explosives as there are limited pathways for acquisition. However, there is currently no capability to link an explosive charge to its source via post-blast trace residues using isotope ratios or trace elements.

Composite Machine Learning Algorithm for Material Sourcing.

This study developed a composite machine learning algorithm for attribution of materials of forensic interest (like ammonium nitrate) to original sources. k-nearest neighbor and random forest models were used for source elimination and classification, respectively, in a two-step, composite algorithm based on particle color, size/shape, and trace element concentration features. Novel approaches for simulation to supplement within-source reference features based on empirically measured multi-lot analyses, an improved hold-one-lot-out method for cross-validation, an assessment of the likelihood of the presence of a reference sample, fusion of the source probabilities from the respective classification models, and the calculation of metrics for assessing ensemble sourcing performance are described.

Highly accurate classification of biological spores by culture medium for forensic attribution using multiple chemical signature types and machine learning.

Future proliferation of biological expertise and new technology may increasingly lower the difficulty to produce biological organisms for misuse. Rapid attribution of a biological attack is needed to quickly identify the person or lab responsible and prevent additional attacks by enabling the apprehension of suspects. Here, triplicate batches of Bacillus anthracis Sterne strain (BaSt) spores were grown in a total of seven amateur and professional media.