Award Information
Description of original award (Fiscal Year 2018, $97,328)
This project continues the research on a new method of body fluid identification and furthers its field capabilities. This method of identification uses Raman spectroscopy and advanced chemometrics to distinguish between body fluids. It is an improvement on current methods because it is non-destructive, with simple sample preparation and confirmatory.
The first goal of this research project is to determine the limit of detection and limit of identification of our current Raman method for sweat and vaginal fluid. The sweat samples used will be from both genders and three races, Caucasian, Hispanic and African American. The vaginal fluid samples will also encompass the three races. For the first goal different volumes of the two body fluids will be deposited and mapped with our Raman microscope. The limit of
identification will be found using statistical models. The limit of identification will be found using the standard analytical method of three times the standard deviation of the noise.
The second goal of the research is to prepare and sample simulated evidence. The simulated evidence will be prepared with blood, semen, saliva, sweat and vaginal fluid from a range of races and genders to encompass all possible variations. Preparation parameters for the evidence will include substrate variation and mixtures of body fluids. Each parameter will first be tested alone so that optimal sampling parameters can be found for each condition.
The final step of the second goal will be to combine all the variables together onto one sample of simulated evidence. Several pieces of evidence will be made in order to encompass several different conditions. Modifications will be made to our current method to account for the effects of different parameters. This research will validate our technique and help ready it for real life application. Annual interim reports will be given as well as a final report. Products from this research will be data sets, analytical figures of merit and possible statistical models. Spectra data will be archived at .spc files, and well as in MATLAB data sets. Statistical models will be saved as .mat files.
"Note: This project contains a research and/or development component, as defined in applicable law," and complies with Part 200 Uniform Requirements - 2 CFR 200.210(a)(14).
ca/ncf