The authors of this paper propose using the fractal nature of fracture surface topography and their transition to non-self-affine properties to define an appropriate comparison scale; they also report on efforts to develop supporting statistical methods for forensic fracture matching through three-dimensional topological imaging of fracture surface details.
The complex jagged trajectory of fractured surfaces of two pieces of forensic evidence is used to recognize a “match” by using comparative microscopy and tactile pattern analysis. The material intrinsic properties and microstructures, as well as the exposure history of external forces on a fragment of forensic evidence have the premise of uniqueness at a relevant microscopic length scale (about 2–3 grains for cleavage fracture), wherein the statistics of the fracture surface become non-self-affine. The authors utilize these unique features to quantitatively describe the microscopic aspects of fracture surfaces for forensic comparisons, employing spectral analysis of the topography mapped by three-dimensional microscopy. Multivariate statistical learning tools are used to classify articles and result in near-perfect identification of a “match” and “non-match” among candidate forensic specimens. The framework has the potential for forensic application across a broad range of fractured materials and toolmarks, of diverse texture and mechanical properties. (Published Abstract Provided)
Downloads
Similar Publications
- Introducing "DoPP": A Graphical User-Friendly Application for the Rapid Species Identification of Psychoactive Plant Materials and Quantification of Psychoactive Small Molecules Using DART-MS Data
- Is the Gender Gap in Overdose Deaths (Still) Decreasing? An Examination of Opioid Deaths in Delaware, 2013–2017
- Coping Patterns over Time and the Association with Stress, Depression and Self-Efficacy Among Adolescents: Latent Transition Analysis