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Application of Laser-Induced Breakdown Spectroscopy to Forensic Science: Analysis of Paint and Glass Samples

NCJ Number
232135
Author(s)
Michael E. Sigman
Date Published
October 2010
Length
44 pages
Annotation
Under the funding provided for this study, a commercial single 1064 nm pulse laser-induced breakdown spectroscopy (LIBS) instrument was purchased and used to assess the potential for using LIBS in the forensic analysis of glass samples, which is a less expensive technology than laser ablation-inductively coupled plasma - mass spectrometry (LA-ICP-MS).
Abstract
The study results show that LIBS, when used in conjunction with refractive index (RI), provides high (greater than 90 percent) discriminating power for several glass types, including beverage glass, automobile headlamp glass, and float glass from automobile side and rear windows. LIBS and RI exhibited a lower discriminating power for automobile side-mirror glass, which is commonly found in forensic casework. A subset of the side-mirror glass that exhibited a small variance in measured RI values, however, was highly discriminated (greater than 90 percent) by LIBS+ RI. A comparative assessment of LIBS and LA-ICP-MS for several common sets of glass samples found LA-ICP-MS to be a more highly discriminating analytical technique, although the analysis time is longer. Based on these findings, the researchers recommend that failure to discriminate questioned and known samples by LIBS or LIBS+RI constitutes ground for reanalysis with a more highly discriminating technique. The authors caution that this study did not address the use of the evolving dual pulse LIBS techniques, which may prove to be more highly discriminating for glass analysis. This report includes a short background review of forensic glass analysis, a brief introduction to LIBS, and a description of the data analysis methods used to determine the discriminating power of LIBS. 10 tables, 4 figures, 30 references, and appended list of scientific presentations resulting from this research along with sample statistical analysis