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Determination of Key Factors in Particle Combination Analysis to Enable Systematic Improvement, Optimization and Transition to Practice

NCJ Number
Date Published
69 pages

This document reports on experiments that focused on the analysis of combinations of very small particles in trace evidence, to address the major limitations of current prevailing methods of trace evidence analysis and facilitate the optimization of routine practice.


The authors report on experiments that utilized newly developed quantitative statistical tools to measure the individuality of particle combinations that are ubiquitous in our environment and abundantly present on common items of evidence. These particle combinations have previously been recognized for their potential but left unused for lack of a practical methodology. A major priority for forensic science research is to increase the value of trace evidence analysis, which is determined by the numbers of cases where the trace evidence is useful and the additional probative value that it can bring. Challenges and limitations of current prevailing methods of trace evidence analysis can result in funding reductions, service restrictions, or a complete closure of trace analysis sections within forensic laboratories. The authors’ research goal was to measure the relative impact of a wide set of independent variables on very small particle (VSP) analysis; the result was the identification of important, controlling factors that must be addressed to meaningfully optimize the protocol. Using 30 specimens of each evidence type, the authors used SEM/EDS as the baseline method for particles analysis of VSP. They also performed analyses of particle combination selectivity. The authors’ presentation of results employs box-and-whisker diagrams to visualize differences and variability in analytical results. The findings confirm abundant, highly discriminating VSP on common items of evidence, and high reproducibility of VSP analyses. The authors discuss the factors that affected strength of correspondence, such as X-ray analysis variables; factors affecting the numbers of detected particles; and factors affecting analytical time and costs.

Date Published: January 1, 2023