Fast identification of inorganic and organic gunshot residues by LIBS and electrochemical methods

Accepted Manuscript Fast Identification of Inorganic and Organic Gunshot Residues by LIBS and Electrochemical Methods Tatiana Trejos, Courtney Vander Pyl, Korina Menking-Hoggatt, Ana Lorena Alvarado, Luis E. Arroyo PII: DOI: Reference:

S2468-1709(17)30151-0 https://doi.org/10.1016/j.forc.2018.02.006 FORC 94

To appear in:

Forensic Chemistry

Received Date: Revised Date: Accepted Date:

15 December 2017 28 February 2018 28 February 2018

Please cite this article as: T. Trejos, C.V. Pyl, K. Menking-Hoggatt, A. Lorena Alvarado, L.E. Arroyo, Fast Identification of Inorganic and Organic Gunshot Residues by LIBS and Electrochemical Methods, Forensic Chemistry (2018), doi: https://doi.org/10.1016/j.forc.2018.02.006

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Title: Fast Identification of Inorganic and Organic Gunshot Residues by LIBS and Electrochemical Methods Authors and affiliations: Tatiana Trejos, Ph.D. 1, Courtney Vander Pyl1, B.S., Korina MenkingHoggatt1, MSc., Ana Lorena Alvarado2, Ph.D., Luis E. Arroyo, Ph.D. 1

Author’s Address: 1

West Virginia University, Department of Forensic and Investigative Science, 208 Oglebay Hall, Morgantown, WV, 26506-6121 2

Centro de Electroquímica y Energía Química, CELEQ, Universidad de Costa Rica, San Pedro de Montes de Oca, San José, Costa Rica.

Authors email: Tatiana Trejos: [email protected] Courtney Vander Pyl: [email protected] Korina Menking-Hoggatt: [email protected] Ana Lorena Alvarado: [email protected] Luis E. Arroyo: [email protected]

Corresponding author: Luis E. Arroyo Assistant Professor West Virginia University, Department of Forensic and Investigative Science, 208 Oglebay Hall, Morgantown, WV, 26506-6121 [email protected]

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Fast Identification of Inorganic and Organic Gunshot Residues by LIBS and Electrochemical Methods Abstract In this study, electrochemical and laser-based spectroscopic methods (LIBS) are proposed as screening methods that are quicker, more selective and more effective than any current fieldtesting technique. These methods offer superior information by simultaneous detection of organic and inorganic gunshot residues, including a substantial number of elements used in modern ammunition. Moreover, the selected analytical scheme permits subsequent confirmatory analysis (SEM-EDS) on the same sample. The rapid scanning of the laser-beam favors the identification of up to 5 different emission lines per target element in less than one minute, with repeatability better than 11% RSD and limits of detection for the species of interest in the range of 0.2-200 ng. Optimization of the electrochemical sensors demonstrated the feasibility of Square Wave Anodic Stripping Voltammetry (SWASV) for the rapid detection of inorganic and organic target compounds using carbon printed disposable electrodes (repeatability <8% RSD, detection limits 0.1-1 ng/µL, linearity > 0.991). The separation and detection of mixtures of Pb, Sb, Cu, DNT, and NG was possible after LIBS analysis, in approximately 3 minutes per sample. A set of 112 samples, 20 samples from non-shooters and 92 samples from 28 shooters, were collected as part of the validation study. Pistol (9 mm and .22) and revolver (.357 Magnum) were fired at indoor and outdoor shooting ranges. Metrics of performance, such as error rates (false positives and false negatives), specificity, sensitivity, and accuracy, indicate the combination of LIBS and electrochemical methods are a reliable and promising approach to advance current practice.

Keywords: gunshot residues; electrochemistry; LIBS; firearm discharge residues; forensic chemistry.

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1. Introduction Rapid and accurate detection of firearm discharge residues is highly desirable in circumstances that require fast response to protect the welfare of citizens and reliable information to make informed decisions. Forensic laboratories provide valuable support to identify a potential shooter, determine firing distances, or differentiate between a potential homicide, suicide, or accidental shooting. The scientific validity of this field relies on extensive research and standardization of the existing methods [1,2].Nonetheless, there are still some remaining challenges in this area in terms of speed of analysis, preservation of the evidence, accuracy and interpretation of results [3-5]. When a gun is fired, a mixture of compounds is expelled from the firearm in the form of vapor and particles. These residues —known as firearm discharge residues (FDR) or gunshot residues (GSR) —can be deposited on the hand and face of a shooter and surrounding areas, or can travel in the direction of the bullet and reach target surfaces such as skin and fabric. The gunshot residues are composed of inorganic components originating from the primer (IGSR), and the organics originating from propellant and stabilizers (OGSR) [4]. The current standard method for GSR analysis on hands is SEM-EDS (ASTM E1588-17) [1].This method relies on the detection of IGSR from the primer (such as Pb, Ba and Sb) and the imaging of the distinctive spherical morphology of the condensed particles. Nonetheless, the method is time consuming, which limits the efficiency of an investigation. The speed of analysis is particularly relevant in this field since the probability of detecting discharge residues decreases rapidly as the time window between the firing and the collection increases. Also, OGSR components could degrade within 4-24 hours after collection, depending of the compound, and storage conditions such as exposure to light and temperature. Common methods used for the detection of GSRs (e.g., SEM-EDS, ICP-MS, AAS, and chromatographic methods) lack portability and versatility to conduct screenings on-site and at the laboratory [2]. Another challenge is the limited capability of these methods to detect only certain organic or inorganic components related to GSR. Moreover, current demands for the detection of GSRs require techniques with expanded capabilities to detect toxic-free ammunitions [3]. Laser ablation spectrochemical methods (LA-ICP-MS, LIBS) represent a promising alternative for rapid detection of IGSR [6,7]. Identification of IGSR in few minutes as opposed to hours is possible with these methods. Nonetheless, the sole detection of inorganic or organic compounds is not always conclusive of a firearm discharge, as false positives are expected due to environmental contaminants. As a result, a variety of methods have been recently proposed, including LC-MS [8-11] and GC-MS [12], time-of-flight secondary ion mass spectrometry (TOF-SIMS) [13], desorption electrospray ionization MS (DESI-MS) [14,15], electrochemical methods (EC) [3,16] , ion mobility spectrometry (IMS) [17] and electro kinetic capillary electrophoresis (MECE) [18]. The ultimate incorporation of these methods in crime laboratories will be driven by their current availability in law enforcement agencies, their ability to provide a versatile and cost-effective solution, and by not impeding subsequent confirmatory inorganic testing (e.g., SEM-EDS).

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This study validated a novel approach that incorporates orthogonal data from LIBS and electrochemical sensors, using sampling methods compatible to SEM-EDS analysis. LIBS is a rapid chemical analysis technique that uses a high energy pulsed laser for the characterization of inorganic elements, isotopes and some organic elements such as carbon, nitrogen and oxygen [19]. A LIBS system is composed of a pulsed laser, an automated ablation stage, a set of lenses, the collection optics and the spectrometer. The interaction of the pulsed laser with the material generates a micro-plasma on the sample surface. This micro-plasma is temporal and typically lasts only few microseconds. As the micro-plasma cools down, the excited species return to their natural ground states, causing emission of light that is then collected and dispersed by a spectrograph in the form of intensity versus wavelength spectrum [20]. Each element emits a series of sharp lines that are associated with specific atomic or ionic transitions, therefore, the selectivity of the technique is usually favored by the multiple emissions of species per element [21]. LIBS technology has demonstrated excellent repeatability and reproducibility with remarkable versatility and detection capabilities that make it suitable for characterization and identification of elemental compositions of materials at major, minor and trace levels [12,22,23]. These advantages are ideally suited to the proposed application. On the other hand, electrochemical detection is a very mature technique that has been applied for decades in areas of analytical chemistry, environmental sciences and health sciences, to mention some [3]. Forensic applications of electrochemistry offer unique advantages for the chemical analysis of poisons, drugs, and explosive materials. Particularly in the case of gunshot residues, the tandem detection of both organic and inorganic residues is highly relevant. These emerging methods have the potential to scale the technology to hand held devices, to target a large variety of species at low detection limits, and to offer simplicity of operation. Electrochemical detectors respond to changes in voltage, or current, induced by the redox reactions of the analytes. In a typical electrochemical experiment, several parameters could be measured including: potential (E, potentiometric), current (I, amperometric) and charge (Q, conductimetric). Therefore, different configurations can be applied to enhance the sensing capabilities [3]. The organic identification of explosives and GSR has been previously reported using cyclic voltammetry (CV) and square-wave voltammetry (SWV). Alternatively, the detection of inorganic elements from IGSR has been reported by anodic stripping voltammetry (ASV), square-wave voltammetry (SWV) and differential pulse cathodic adsorptive stripping voltammetry (DPCAdSV). Common electrodes for the detection of GSR are the mercury glassy carbon electrode, hanging mercury drop electrode and modified carbon electrodes [24-31]. More recently, the use of disposable electrodes has been reported for the simultaneous detection of IGSR and OGSR. Advantages of these electrodes are portability, low cost, potential to be used for direct sampling of GSRs and the non-destructive nature of the electrochemical process that allows further confirmatory testing. The aim of the present study was to develop and validate a practical approach to combine spectral (LIBS) and electrochemical data to enhance the value of traditional protocols used for the detection of firearm residues.

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2. Material and methods 2.1. Sample Preparation and Collection The collection and analytical approach were developed to be compatible with subsequent confirmatory methods (SEM-EDS) on the same sample. Double-coated carbon conductive tabs (PELCOTM, TedPella, CA) were mounted on graphite planchets (TedPella, CA) and over SEMEDS aluminum stubs (TedPella, CA), and stored on single mount storage tubes commonly used by law enforcement personnel and forensic practitioners. Each sampling set consisted of 4 stubs for GSR collection from known shooters (palm and back of both the left and right hand), and one stub for collection of negative controls. Negative controls were collected from a single hand (either left or right hand) of individuals who had not fired a gun in the last 24 hours, and from the palm and back areas collectively. A total of 112 samples were collected from the left and right hands of 28 shooters (92 stubs) and 20 non-shooters (20 stubs). Two sampling stubs were applied to the hands of the first ten shooters (left and right hand), while four stubs were applied to the hands of the remaining 18 shooters (left, right, palm, back). Gunshot residues were collected less than 30 minutes after firing a gun. Different firearms and ammunitions were fired at WVU-FIS ballistics laboratory under controlled environmental conditions, and at an outdoor shooting range during the Summit Betchel Reserve, National Scout Jamboree in WV (Table 1). Samples were then stored in pre-labeled cardboard boxes, and placed inside Ziploc bags and plastic storage containers at the laboratory. Nitrile gloves (Fisher Scientific, NH) and lab coats were worn during collection and analysis, and negative control blanks were analyzed routinely as part of the respective daily instrumental performance tests. 2.2. Analytical methods The analytical approach was developed to allow subsequent analysis on the same sample, first by LIBS, then followed by EC sensors. Method optimization was conducted using response surface Box Behnken experimental designs, using standard solutions of known concentrations, then evaluating the methods with a validation set of samples collected from shooters and nonshooters. SEM-EDS imaging and elemental analysis (JEOL 6490LV) was conducted on some samples after the screening methods following the ASTM E1588-17. [1]

2.2.1. LIBS method A 266 nm 10 ns Nd-YAG laser (J200, Applied Spectra, CA) was used for the LIBS experiments. The laser-beam was scanned across the carbon conductive adhesive using a continuous ablation line of 100 µm by 7 mm. The laser was fired at ~15 mJ per pulse, 10 Hz frequency, speed of 150 µm/s, and using argon gas (1 L/min, ultrahigh purity, Matheson, WV). The ablation cell inserts were modified to fit standard SEM-EDS stubs in the ablation chamber with no additional manipulation of the conductive tab.

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Method optimization was conducted on standards prepared by spiking 50 ng to 25 µg of Pb, Ba, Sb, Cu and Al (ICP-MS quality, SPEX Certiprep) over a surface of approximately 1cm2 of Whatman paper #42 (Fisher Scientific), and over carbon adhesives, then dried overnight. Control blanks were measured as part of the optimization study to determine that no contamination was derived from the sampling substrates. Limits of detection were calculated as three times the standard deviation of the background (at wavelength close to the analyte peak, n = 7) divided by the slope of the calibration curve as recommended in the literature [21, 32], then confirmed by measuring standard samples at concentrations near the expected LOD. 2.2.2. Electrochemical method Electrochemical sensors were processed by a Metrohm Autolab 128N workstation operated for cyclic-square wave voltammetry (c-SWV). Disposable Carbon and Gold Screen Printed Electrodes (DS110 and DRP-220AT, Dropsense) were used for sampling and analysis. Individual solutions and mixtures of inorganic and organic components commonly found in GSR were prepared for the method optimization (1-10 ng/µL solutions of Pb, Ba, Sb, Cu, NG, 2,4DNT Cerilliant, TX), then an aliquot of 50 µL was added to the electrode’s surface. Different concentrations of sodium acetate buffer (pH 4.5) were evaluated as electrolyte during the optimization stages. Limits of detection were estimated as 3.3 times the standard error divided by the slope of the calibration curve, using the areas of the analytical signals, as commonly reported for electrochemical data [33,34]. 2.3. Data preprocessing and statistical analysis Background subtraction, peak identification, and integration of the LIBS spectral data was conducted using Aurora software (Applied Spectra) and then processed using Excel 2016 (version 15.24, Microsoft Corporation). Electrochemical data was pre-processed using NOVA Software (Rev 2.12). JMP Pro 13 (v.2016, SAS Institute Inc., NC) was used for further exploratory data analysis and data mining.

3. Results and Discussion 3.1. Evaluation of sampling methods The central hypothesis of this study is that electrochemical and laser-based spectroscopic techniques (LIBS) will enhance the efficacy of current detection of firearm discharge residues. The hypothesis has been formulated, based on preliminary findings that demonstrate these methods offer superior information by the simultaneous detection of organic and inorganic components. The combination of LIBS and electrochemistry was conceived as a practical approach, given the potential of both methods to provide fast screening in just few minutes, high specificity, orthogonal information, and minimally invasive capabilities. In addition, the methods are cost-effective and easy to operate. Moreover, the instrumentation is easy to adapt for laboratory or portable/satellite operations. For instance, electrochemical units are small, lightweight and battery-operated and therefore can be depleted for direct detection in the field. Although the LIBS used in this study is not a hand-held device, the instrument configuration allows for installation in a mobile laboratory. A fast screening method with such advantages is not currently available for laboratory or field-testing. 6

A priority during the method optimization was to adapt the sampling process to be compatible with SEM-EDS analysis. The reasoning for this decision is that SEM-EDS remains the standard method for confirmatory analysis of IGSR, and therefore having a universal sample collection method would facilitate technology transfer in the future. One of the limitations of SEM-EDS, however is the duration of the analysis, which typically requires several hours or days to confirm the presence or absence of GSRs, limiting the added value in the investigations. Hence, the proposed methods were designed to speed up and enhance GSR information, while allowing further confirmation by SEM-EDS when necessary. From a practical perspective, the proposed approach was strategically developed to avoid modifications in the current SEM-EDS sampling methods using common carbon adhesive tabs. A key experiment to demonstrate applicability of the carbon adhesives consisted in evaluating whether or not the substrate contributed to high background levels of the species of interest. The carbon adhesives were mounted on inert Teflon and analyzed by LIBS and EC. Fortunately, with the exception of aluminum, the background levels on the adhesive were negligible. Then, a second question to answer was whether or not the metals from the pin stub specimen mount represented a source of contamination during analysis. Two approaches were initially evaluated for this purpose: a) mounting the carbon adhesive stubs on graphite planchets, and b) placing two layers of carbon adhesive directly on top of the aluminum mounts. The spectra and voltammograms were compared to those obtained from the carbon adhesive mounted on Teflon. Since LIBS and electrochemical analysis are interacting primarily with the surface of the adhesive, both sampling methods proved to have minimal contribution, if any, on the background signal of the analytes of interest (Pb, Ba, Sb, Ca, Si, Cu, DPA, NG, DNT). Moreover, it was noticed that the graphite planchets reduced the adhesive properties of the carbon stubs over time, posing a risk of losing the adhesive during the application of the stubs to the hands of individuals. As a result, the second approach was chosen as it demonstrated to be suitable, more cost-effective and in alignment with current SEM-EDS sampling practices. In order to allow minimal alteration of the substrate, the LIBS beam was scanned across the carbon adhesive at fast speed while interacting with the GSR particles attached to the adhesive. The penetration depth of the laser beam into the adhesive layer was estimated under microscopic examination to be less than 5 µm. Figure 1 illustrates the superficial damage of the adhesive after ablation. Approximately 0.06% of the surface of the stub was used for the ablation process, leaving most of the surface of the stub unaltered for further analyses. This becomes important if SEM-EDS is later conducted, as the ASTM standard method allows the flexibility of partial analysis of the surface area due primarily to the extensive time required for a total surface area analysis. The efficiency of electrochemical analysis on the carbon adhesive was evaluated by; a) rubbing the carbon adhesive directly on the electrode and physically transferring the particles on the electrode’s surface, b) using 50 µL of 0.1 M acetate buffer (pH 4.5) as electrolyte to partially remove the mixture of metals and organic compounds from a portion of the adhesive substrate, then depositing the solution on the electrode, c) using an aliquot of 50 µL of acetonitrile to partially remove GSR from the adhesive, transfer the acetonitrile to an Eppendorf tube, let it dry, and reconstitute with 50 µL from a second wash with 0.1 M acetate buffer (pH 4.5). The option c 7

provided better recoveries, and demonstrated that some GSR particles still remained on the adhesive after the mild washing procedure. Moreover, GSR particles transferred from the carbon adhesive to the electrode surface maintained their morphology after the electrochemical analysis, permitting further SEM-EDS analysis directly from the electrode surface or from the remaining carbon stub. One critical advantage of this approach is that the methods are minimally invasive because they only require a small surface from the stub, allowing LIBS analysis, followed by electrochemical analysis, and if needed, additional SEM-EDS confirmation. Figure 2 illustrates an example of SEM-EDS detection of characteristic GSR particles after LIBS and EC screening, where the morphology and chemical composition of the GSR particles remained unaltered. As a result, this approach offers a solution that could become particularly useful for investigations requiring quick decision-making. Another benefit of this approach is that although the methods are proposed as screening tests, their reliability is superior to typical analytical screening [35] and therefore they have the potential to provide confirmatory value and add certainty to the interpretation of the evidence.

3.2. LIBS method optimization Response surface experimental design was used to find the optimal ablation and detection parameters. Variables optimized included gate delay, gas flow, laser energy, laser frequency and scanning speed. Optimal signal-to-noise and reproducibility of the measurements were achieved by selecting the parameters described above in 2.2.1. The rapid scanning conditions permitted LIBS analysis times of less than one minute per sample. The simultaneous identification of 2 to 5 different emission lines per target element increases the confirmatory value and selectivity of the LIBS method. For instance, figure 3 shows a typical LIBS spectrum from a sample collected from the hand of a shooter, where multiple emission lines are observed for the main elements associated with IGSR: Pb, Ba, and Sb. The detection of barium was confirmed by at least five atomic and ionic emission lines (455.4 nm (II), 493.3 nm (I), 553.4 nm (I), 614.1 nm (II), and 705.9 nm (I)), while lead and antimony were monitored at two main atomic lines (Pb 368.3 nm (I), Pb 405.8 nm (I)), Sb 252.8 nm (I), Sb 259.8 nm (I), respectively). Moreover, the multi-element capability of the LIBS method permitted the detection of other elements commonly associated with modern ammunition (e.g., Al, Ca, Si, Sn, Zn, Cu, Ti, Sr) and other elements that help rule out external sources of contamination. This is an important advantage of the method as several studies have shown that not all the GSR particles contain Pb, Ba and Sb, and other primers and ammunitions may contain a broader suit of components. LIBS and electrochemical methods are suitable for quantitative analysis, however due to the fact that our approach provides bulk identification of GSR components rather than an individual characterization of GSR particles, the data was considered semi-quantitative or qualitative in nature. Despite this, some quantitative figures of merit are still relevant for method validation, in particular the detection capability, analytical selectivity, linearity, reproducibility and repeatability of the measurements. Limits of detection showed the method is capable of 8

identifying a variety of elements at levels that allow identification of GSR particles collected from hands of a suspect (Table 2). It is important to note, that unlike other fully “bulk” techniques such as ICP-MS and AA, the LIBS method does not consume the totality of the sample and provides valuable spatial information of the GSR composition, as the spectra is collected per every shot. Calibration curves were prepared by spiking 50 ng to 50 µg of mixture solutions into an area of 1.5 cm2 of Whatman paper # 42, and onto the carbon substrate. The mass removed by the ablation process represents approximately 0.3% of the total spiked area on the paper and 0.06% of the total spiked area on the adhesive, therefore the actual mass ablated ranged from 2 ng to 200 ng. Figure 4 illustrates the barium calibration curve (bottom) and the respective spectra signal (top) for ablated masses ranging from 6.5 ng to 220 ng. Seven measurements were conducted per standard, and two different analysts repeated the experiments on two separate days. Linearity better than 0.985 was obtained for Pb, Ba and Sb, with repeatability between replicate measurements better than 11% RSD, and inter-day and inter-analyst reproducibility better than 15% RSD. Nonetheless, variability of the measurements on sampling stubs applied to the hands of a shooter are anticipated to be higher than the variability reported on controlled standards, as the amount and location of GSR particles within a stub is a random event and difficult, if not impossible, to reproduce. The variability from actual GSR samples was therefore assessed as the capability of the method to detect elements associated with GSR above a threshold value in a given stub. As a result, the accordance was evaluated as the capability of the method to produce similar positive results from replicates of the sample. The positive threshold was established when the analyte signal was firstly above the LOD, and secondly exceeded the mean background signal (mean non-shooter, negative control) by 3 standard deviations. A set of ten samples collected from ten individuals that shot a revolver or a pistol, and ten stubs collected from the hand of non-shooters was used for the variability study. For purposes of this experiment, a single stub was applied to the back and palm areas collectively; non-shooter samples were collected from one hand only, while shooter samples were collected from both hands separately. Each sample was measured three times, and in all instances the same number of positive results were achieved. Moreover, the pistol samples were measured one week after firing, one month after firing, and three months after firing. Similar results on the same stubs were obtained after 3-month period, demonstrating the inorganic constituents persisted once they were deposited on the carbon tab. In contrast, the organic constituents, measured by electrochemical methods, were rapidly lost when measured after one week of collection. The results are in agreement with previous studies on GSR persistence [5,17,36], stressing the importance of providing fast screening methods for improved success on detection of OGSR.

3.3. Electrochemical method optimization The electrochemical method focused on the use of disposable carbon screen-printed electrodes that permit future laboratory and field-based testing. Disposable Carbon and Gold Screen Printed Electrodes were initially tested using mixtures of inorganic (Pb, Sb, Cu) and organic (DNT, NG) 9

components. The carbon printed electrodes produced better signal to noise ratios and therefore they were selected for the rest of the optimization and validation studies. In this technique, the electrochemical process consists of two major steps: a pre-concentration step and a stripping step. During the pre-concentraiton step, the analyte species in solution are reduced (accumulated) at the surface of the working electrode. Then, the electrode is scanned linearly towards positive potentials so that metals (e.g. Pb, Sb,) are stripped from the electrode and re-oxidized at a potential characteristic of each metal. Therefore, parameters with high influence on the analytical response are the potential step (Estep), the square wave amplitude (mV) and frequency (Hz). These parameters were optimized to obtain maximum sensitivity, measured as the highest signal to noise ratio, while maintaining good peak resolution precision and discrimination from background. The reduction of Pb+2 and Sb+3 to their respective metallic forms during the pre-concentration step is straightforward. However, for the organic analytes it is important to highlight their reduction mechanism to illustrate the capability of the proposed detection, since both metals and organic compounds are being reduced simultaneously. As an example, the reduction mechanism of 2,4-DNT in aqueous solutions involves the formation of a N-hydroxyamino group on each nitro group in a single four proton/four electron reduction wave as follows [37]:

In the case of nitroglycerin, the generation of an alcohol group and a nitrite is expected to occur during the reduction step. An optimized reduction potential of -0.95 V and an accumulation time of 120 seconds were found to provide acceptable measurements. The forward scan, or the anodic stripping process, produces the oxidation of the analytes in solutions as described in figure 5. This figure also shows the power of the electrochemical technique to simultaneously resolve both organic and inorganic analytes in less than 3 minutes. Sharp oxidation peaks were observed for the studied analytes with acceptable reproducibility (<8 % RSD). In the case of 2,4-DNT however, the peak is significantly broader (~0.2V wide) and the center of the peak tends to shift slightly at higher concentrations. As a result, a larger acceptable window was used for the integration of 2,4-DNT signals. The inset in figure 5 shows the picture of the electrode, the black area represents the electrode surface where 50 µL of the mixture is deposited prior analysis. As mentioned earlier, one of the advantages of electrochemical detection is simultaneous identification of inorganic and organic 10

compounds, which enhances the reliability of the identification of GSR. Moreover, LIBS and electrochemical methods complement each other in terms of sensitivity to certain species (Table 2). For instance, barium was not detected by the electrochemical method due to its highly negative oxidation potential, however it is easily detected by LIBS. On the other hand, EC methods detected lower concentrations of lead than LIBS. For instance, in a set of 28 shooter samples measured by both methods, 11 samples showed non-detectable lead by LIBS while only 6 of those were not detected by EC. While LIBS and EC provide orthogonal information, the confirmation of similar IGSR species by two different and independent methods also enhances the certainty associated with the detection of GSR species (e.g., detection of Pb, Sb, Cu by two separate methods).

3.4 LIBS and Electrochemical method validation The reliability of the methods was assessed using a qualitative validation approach because the ultimate outcome of the analysis is a binary decision about the presence or absence of certain GSR compounds [38,39]. A total of 112 samples were analyzed from 20 non-shooters and 28 shooters. It is worth noting that the terminology “shooter” and “non-shooter” is used in the manuscript within the context that the specimens were collected under controlled conditions, where the activity of the individuals was known. Nonetheless, in a real case, the term “shooter” is not commonly used, as it is problematic to definitively conclude that a subject did discharge a weapon as opposed to being in proximity with a discharge or with having received particles as the result of a transfer. Based on the determination of presence or absence of GSR constituents, the data was then classified into two categories given a specified threshold or criteria (e.g., shooter or non-shooter). From these categories, four outcomes are possible: 1) false positive (FP) is obtained when a sample from a non-shooter is classified as a shooter based on the presence of GSR components, 2) false negative (FN) is obtained when a sample from a shooter is classified as non-shooter based on the absence of GSR components, 3) true negative (TN) is a sample from a non-shooter correctly classified as non-shooter due to absence of GSR components, and 4) true positive (TP) is a sample from a shooter correctly classified as a shooter based on the presence of GSR components. The reliability of the proposed analytical scheme was then assessed by the following performance rates: 1. False positive rate (FPr), which is a measure of the probability of misidentifying a known negative sample (i.e. non-shooter) as a positive result (i.e. GSR presence, shooter classification) when a given analytical process is executed. 2. Specificity, which is a measure of the probability of obtaining a negative result given that no GSR is present. Specificity is the ability of the analytical process to correctly achieve a negative result from true negative samples.

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3. False negative rate (FNr), which is a measure of the probability of misidentifying a known positive sample (i.e. shooter) as a negative result (i.e. GSR absence, non-shooter classification) when a given analytical process is executed. 4. Sensitivity, which is a measure of the ability of the analytical process to achieve correct results for samples known to contain GSR (i.e. rate of true positives).

As a first step, box plots were constructed to visualize the distribution of the data for the two main categories. Due to the lack of a suitable internal standard for the LIBS method, the signal to noise ratios, rather than a quantitative concentration value, were used as a way to normalize and compute the data. Figure 6 shows the distribution and variability of the LIBS data from nonshooters and shooters, including each separate stub sampled from every individual. Some low values from shooters are close to the non-shooter quartiles for those stubs that returned negative results, such as lower levels on one hand versus the other. However, in general the box plots show higher values in the distribution of Pb, Ba and Sb from shooters than non-shooters. Relatively small variability was observed among non-shooters, where most of the samples were close or below detection limits. Larger variability is observed from the shooters set, where samples that detected larger amounts of GSR are outside of the 75% quartile. The signals of Ca, Si and Al were also monitored during the experiment, as some combinations of these elements with Pb or Ba are considered consistent with IGSR. Nonetheless, the Ca, Si and Al content did not provide relevant information in this set, as the values from non-shooter samples are not significantly different from the shooter samples, and therefore these elements were not further considered for the data interpretation (Figure 6). Given that the lower whiskers of the distribution of shooters has some overlaps with the upper tail of non-shooters, a question is how often false positives and false negatives occurred in the validation set. This question was addressed using two different procedures, by comparing each individual sample to a critical threshold value and by using discriminant analysis (DA) as a prediction tool for classification of the data into shooters and non-shooters categories. An exploratory evaluation of the data was conducted by estimating how often non-shooter samples and shooter samples were above the critical threshold value. The presence/absence of gunshot residues on the hands of a shooter depends on several factors, such as the manner the gun is held during and after the shooting, any post-shooting contact between hands, and postshooting activities (touching the face, the hair, the clothing, etc.). Therefore, for each shootersample there are three main possible outcomes: 1) only one of the stubs contains GSR, 2) more than one of the stubs contains GSR, or 3) none of the stubs contains GSR. A positive identification of GSR was determined if at least one of the four stubs per individual returned a positive result for Pb, Ba and Sb, or if at least two of the 3 elements were present above threshold (Pb/Ba, Ba/Sb or Pb/Sb). Using these criteria, only one out of 20 background samples produced a false positive, containing Ba and Sb signals above the average threshold (5% false positive), while all 28 shooter samples were successfully identified as positive. From the 28 shooters, 17 of the samples showed at least one of the stubs with Pb, Ba and Sb above the threshold and the remaining 11 showed positive thresholds for 2 of the 3 target elements, demonstrating that the proposed LIBS method is valuable for IGSR detection (Table 3).

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In addition, one stub of each of the 28 shooters and 20 non-shooters were further analyzed by EC, after LIBS analysis. The number of samples containing Pb above the positive threshold increased with electrochemical detection (22 vs. 17 out of 28 samples). Table 3 shows that supplementary identification of organic species, either NG, 2,4-DNT or both, was found in a majority of the samples. It is worth highlighting that samples with low detection success for organic constituents corresponded to those stubs analyzed more than two weeks after the shooting. Alternatively, a second assessment of the method was conducted by evaluating only one stub per individual and using discriminant analysis to evaluate the success of classifying the samples into shooters or non-shooters categories (table 4). The results for LIBS show 5% false positive rate (stubs from non-shooters classified as a shooter) and 25% false negative rate (stubs from known shooters predicted as non-shooters). Two additional measures derived from these validation rates are the accuracy of the method and the likelihood ratio. The accuracy is as an indicator of the “correctness” of the methods, and considers both correct determinations and error rates. The likelihood ratio rate is an indicator of the informative value of the methods. The larger the LR, the greater the probability of reporting a positive result when GSR are present than when absent. Accuracy of the LIBS method was then estimated as 83% with a likelihood ratio of 95 demonstrating the method is a promising tool for GSR detection. Furthermore, results indicate that the combination of LIBS and EC data enhanced the individual performance of each method, providing superior sensitivity (96%) and specificity (100%), with low error rates (4% false negative, 0% false positive) and high accuracy (98%), therefore providing a robust approach for identification of gunshot residues on hands of individuals of interest. Likelihood ratios were not estimated for the combined methods, because the false positive rate used as the denominator of the ratio was zero. A larger data set that include worsecase scenarios of non-shooter background may provide a more representative estimation of the false positive rate. Indeed, it is worth pointing out that the error rates are dependent on the sample type and sample size selected for a particular study. Therefore, the performance measures reported here —although valuable as a proof of concept and method validation—cannot be generalized yet. This study demonstrates the value of combining two rapid methods that are selective and sensitive to improve current practice. A follow-up research project in our group includes the use of a larger dataset to allow probabilistic interpretation of the data using deep machine learning prediction algorithms, such as neural networks. 4. Conclusions As a result of the many challenges of firearm discharge residues examinations, there is a need to develop complementary practical methods that allow the detection of IGSR and OGSR. These methods should provide rapid screening on-site and at the laboratory, as well as the incorporation of chemical patterns derived from multiple sensors for the assessment of decision thresholds and interpretation of the evidence.

13

This study aimed to develop a practical, simpler, faster and superior approach that overcomes the main challenges of speed of analysis and accuracy of GSR using LIBS and electrochemical sensors. The forensic significance of the proposed methods was thoroughly evaluated in this paper. A notable advantage of these methods is the capability to conduct laboratory-based analysis and field detection of both inorganic and organic components. The approach has shown added value to conventional methods such as: a) Speed and ease of analysis: The LIBS micro beam can be scanned across a target in seconds providing simultaneous detection of multiple elements without sample preparation. Also, electrochemical sensors were adapted and optimized for fast (minutes) in-situ analysis of residues, and require minimally trained operators. The average time of analysis to process a typical set of 4 stubs per individual, a negative control and a positive control can be accomplished under 15 minutes with dual confirmation from LIBS and EC sensors. The unprecedented speed of analysis of the methods provides a unique alternative for casework and intelligence operations that require quick turn-around time of laboratory results. b) Minimal-destructive capabilities: The target material is minimally damaged during the procedure, enabling subsequent sampling or analysis by other means. This is critical for laboratory confirmations by SEM-EDS. c) Superior detection capabilities: LIBS can detect most of the elements in the periodic table, expanding current capabilities to a larger suite of elements associated with modern ammunitions, while electrochemical sensors can detect a large number of IGSR and OGSR components in the low ppm. d) Superior selectivity and reliability: LIBS has the capability to detect multiple atomic and ionic emission lines per element, facilitating the reduction of false positives. Electrochemical detectors were optimized with high selectivity for the redox potential of the target species. Moreover, the information derived from these methods is complementary and enhances the certainty in the results. A good performance of the methods is revealed by the low error rates obtained for the validation set. e) The combination of LIBS and EC provided high sensitivity (96%) and specificity (100%) for the classification of categories based on presence/absence of GSRs, with low error rates (4% false negatives and 0% false positives). An accuracy of 98% was estimated for the particular validation set evaluated in this study. The methods proposed here have the potential to become a transformative platform for enhancing the validity and efficiency of GSR detection at crime laboratories and other law enforcement agencies. It is anticipated that the implementation of the proposed screening methods could reduce backlogs in forensic laboratories, reduce overall costs of analysis and represent a promising alternative for onsite and mobile-lab applications that require fast response and efficient decision-making. Ongoing research in our group includes the use of a larger collection set to further validate the analytical approach and to develop predictive modeling and data fusion for the interpretation of firearm discharge residues evidence.

14

5. References [1] ASTM E30 Committee, Standard Practice for Gunshot Residue Analysis by Scanning Electron Microscopy/Energy Dispersive X-Ray Spectrometry, ASTM E 1588-17, (2017) ASTM International: West Conshohocken, PA, pp. 1-5 [2] O. Dalby, D. Butler, J.W. Birkett, Analysis of Gunshot Residue and Associated Materials: a Review, J. For. Sci. 55 (2010) 924–943. [3] A.M. O'Mahony, J. Wang, Electrochemical Detection of Gunshot Residue for Forensic Analysis: a Review, Electroanalysis. 25 (2013) 1341–1358. [4] M. Maitre, K.P. Kirkbride, M. Horder, C. Roux, A. Beavis, Current perspectives in the interpretation of gunshot residues in forensic science: A review, Forensic Science International. 270 (2017) 1-11. [5] L.S. Blakey, G.P. Sharples, K. Chana, J.W. Birkett, Fate and Behavior of Gunshot Residue: A Review, J. For. Sci. (2017) 1-11. [6] M.J. Silva, J. Cortez, C. Pasquini, R.S. Honorato, A.P.S. Paima, M.F. Pimentel, Gunshot Residues: Screening Analysis by Laser-Induced Breakdown Spectroscopy, J. Braz. Chem. Soc. 20 (2009) 1887-1894. [7] C.R. Dockery, S.R. Goode, Laser-Induced Breakdown Spectroscopy for the Detection of Gunshot Residues on the Hands of a Shooter, Applied Optics. 42 (2003) 6153-6158. [8] J.L. Thomas, D. Lincoln, B.R. McCord, Separation and Detection of Smokeless Powder Additives by Ultra Performance Liquid Chromatography with Tandem Mass Spectrometry (UPLC/MS/MS), J. For. Sci. 58 (2013) 609-615. [9] D. Laza, B. Nys, J.D. Kinder, A. Kirsch-De Mesmaeker, C. Moucheron, Development of a Quantitative LC-MS/MS Method for the Analysis of Common Propellant Powder Stabilizers in Gunshot Residue, J. For. Sci. 52 (2007) 842–850. [10] Benito, Z. Abrego, A. Sánchez, N. Unceta, M.A. Goicolea, R.J. Barrio, Characterization of Organic Gunshot Residues in Lead-Free Ammunition Using a New Sample Collection Device for Liquid Chromatography–Quadrupole Time-of-Flight Mass Spectrometry, For. Sci. Int. 246 (2015). [11] A.L. Gassner, C. Weyermann, LC–MS Method Development and Comparison of Sampling Materials for the Analysis of Organic Gunshot Residues, For. Sci. Int. 264 (2016) 47–55. [12] A. Tarifa, J.R. Almirall, Fast Detection and Characterization of Organic and Inorganic Gunshot Residues on the Hands of Suspects by CMV-GC–MS and LIBS., Sci. Justice. 55 (2015) 168-175.

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[13] C.M. Mahoney, G. Gillen, A.J. Fahey, Characterization of Gunpowder Samples Using Time-of-Flight Secondary Ion Mass Spectrometry (TOF-SIMS), For. Sci. Int. 58 (2016) 3951. [14] R.V. Taudte, A. Beavis, L. Blanes, N. Cole, P. Doble, C. Roux, Detection of Gunshot Residues Using Mass Spectrometry, BioMed. Research Int. 2014 (2014) 1-16. [15] M. Morelato, Screening of Gunshot Residues Using Desorption Electrospray Ionisation– Mass Spectrometry (DESI–MS), For. Sci. Int. 217 (2012) 101-106. [16] J. Wang, Electrochemical Sensing of Explosives, Electroanalysis. 19 (2007) 415-423. [17] S. Bell, L. Seitzinger, From Binary Presumptive Assays to Probabilistic Assessments: Differentiation of Shooters From Non-Shooters Using IMS, OGSR, Neural Networks, and Likelihood Ratios, For. Sci. Int. 263 (2016) 176-185. [18] N. DM, Gunshot Residue Analysis by Micellar Electrokinetic Capillary Electrophoresis: Assessment for Application to Casework. Part II, (2001) 1-13. [19] E. Haddad, J., L. Canioni, B. Bousquet, Good Practices in LIBS Analysis: Review and Advices, At. Spectrosc. 101 (2014) 171-182. [20] L. Radziemski, D. Cremers, A Brief History of Laser-Induced Breakdown Spectroscopy: From the Concept of Atoms to LIBS 2012, Spectrochimica Acta Part B: At. Spectros. 87 (2013) 3-10. [21] D.W. Hahn, N. Omenetto, Laser-Induced Breakdown Spectroscopy (LIBS), Part II: Review of Instrumental and Methodological Approaches to Material Analysis and Applications to Different Fields, Appl. Spectrosc. 66 (2012) 347-419. [22] J. Rakovský, P. Čermák, O. Musset, P. Veis, A Review of the Development of Portable Laser Induced Breakdown Spectroscopy and Its Applications, At. Spectrosc. 101 (2014) 269287. [23] R.E. Russo, Ru, X. Mao, H. Liu, J. Gonzalez, S.S. Mao, Laser Ablation in Analytical Chemistry: A Review, Talanta. 57 (2002) 425-451. [24] M. Lu, K.E. Toghill, M.A. Phillips, R.G. Compton, Anodic Stripping Voltammetry of Antimony at Unmodified Carbon Electrodes, Int. J. Environ. Anal. Chem. 93 (2013) 213-227. [25] J. Wang, B. Tian, Stripping Analysis Into the 21st Century: Faster, Smaller, Cheaper, Simpler and Better, Anal. Chim. Acta. 385 (1999) 429-435. [26] C.A. Woolever, H.D. Dewald, Differential Pulse Anodic Stripping Voltammetry of Barium and Lead in Gunshot Residues, For. Sci. Int. 117 (2001) 185-190. [27] S. Erden, Z. Durmus, E. Kılıç, Simultaneous Determination of Antimony and Lead in Gunshot Residue by Cathodic Adsorptive Stripping Voltammetric Methods, Electroanalysis. 23 (2011) 1967-1974. [28] J.A. Rodriguez, I.S. Ibarra, C.A. Galan-Vidal, M. Vega, E. Barrado, Multicommutated Anodic Stripping Voltammetry at Tubular Bismuth Film Electrode for Lead Determination in Gunshot Residues, electroanalysis. 21 (2009) 452-458. [29] M.O. Salles, J. Naozuka, M. Bertotti, A Forensic Study: Lead Determination in Gunshot Residues, Microchem. J. 101 (2012) 49-53. [30] M. Vuki, K.K. Shiu, M. Galik, A.M. O'Mahony, J. Wang, Simultaneous Electrochemical Measurement of Metal and Organic Propellant Constituents of Gunshot Residues, Analyst. 137 (2012) 3265-3266. [31] A.M. O'Mahony, I.A. Samek, S. Sattayasamitsathit, J. Wang, Orthogonal Identification of Gunshot Residue with Complementary Detection Principles of Voltammetry, Scanning

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Electron Microscopy, and Energy-Dispersive X-Ray Spectroscopy: Sample, Screen, and Confirm, Anal. Chem. 86 (2014) 8031-8036. [32] E. Tognoni, G. Cristoforetti, Signal and Noise in Laser Induced Breakdown Spectroscopy: An Introductory Review, Opt. Laser Technol. 79 (2016) 164-172. [33] I. Lavagnini, R. Antiochia, M. Franco, A Calibration-Base Method for the Evaluation of the Detection Limit of an Electrochemical Biosensor, Electroanalysis. 19 (2007) 1227-1230. [34] E. Desimoni, B. Brunetti, About Estimating the Limit of Detection by the Signal to Noise Approach, Pharm. Anal. Acta. 6 (2015) 1-4. [35] B.L. Mil’man, L.A. Konopel’ko, Uncertainty of Qualitative Chemical Analysis: General Methodology and Binary Test Methods, J. Anal. Chem. 59 (2004) 1128–1141. [36] R.V. Taudte, C. Roux, A. Beavis, Stability of Smokeless Powder Compounds on Collection Devices, For. Sci. Int. 270 (2017) 55-60. [37] P. Buhlmann, E.J. Olson, I. W. C. Isley, J.E. Brennan, C.J. Cramer, Electrochemical Reduction of 2,4-Dinitrotoluene in Aprotic and pH Buffered Media, Int. J. Phys. Chem. C. 119 (2015) 13088-13097. [38] S.L.R. Ellison, Uncertainties in Qualitative Testing and Analysis, Accred. Qual. Assur. 5 (2000) 346–348. [39] S.L.R. Ellison, T. Fearn, Characterising the Performance of Qualitative Analytical Methods: Statistics and Terminology, Trends Anal. Chem. 24 (2005) 468-476. 6. Acknowledgements The authors would like to thank Professor Keith Morris for his assistance in the collection of samples at WVU Ballistics laboratory. Dr. Gerald Lang, Aaron Brake (WVU Department of Forensic and Investigative Science) and the National Scout Jamboree are acknowledged for their support and coordination of the sampling at outdoors shooting range. Table 1. List of firearms and ammunition used in the collection from shooter’s hands. Sampling Set/ Set A ( GSR 01APt to 05A-Pt) Sample ID

Set B (GSR 01B-Rv to 05B-Rv)

Set C (GSR 01CPt to 05C-Pt, 1618C-Pt)

Set D (GSR 101CPt to 110C-Pt)

Revolver, Taurus 38 Special

Pistol, SIG Sauer Mosquito

Pistol, XD® Springfield Armory

Reloaded

Reloaded

OEM -Federal Premium Champion

Reloaded

Bullet

Lead Missouri Bullet Co

Berry's Hollow Point

Lead Round Nose

Berry’s Hollow Point

Bullet weight

115 grain

158 grain

40 grain

124 grain

Firearm

Ammunition

Pistol, HI-POINT Model C9

17

Gunpowder type

Accurate #2 Powder

Accurate #2 Powder

information not available

Accurate #2 Powder

Gunpowder weight

4.0 grain

4.5 grain

information not available

4.0 grain

Primer type

CCI #500 small pistol primers

Remington #1 1/2 small pistol primer

Federal Premium (Pb, Ba, Sb)

Caliber

9mm Luger

0.38 Special

0.22 Long Rifle

9 mm Luger

Firing site

Indoor- WVU Ballistics Lab

Indoor- WVU Ballistics Lab

Outdoor- NSJ

Indoor- WVU Ballistics Lab

CCI #500 small pistol primers

Table 2. Limits of detection for LIBS and electrochemical methods LIBS Analyte Pb

LOD (ng) 80 ± 3 50 ± 4 0.7 ± 0.08 0.2 ± 0.02 1.1 ± 0.04 1.4 ± 0.04 2.1 ± 0.1

Wavelength (nm) 368.3 (I) 405.7 (I) 455.4 nm (II) 493.3 (II) 553.4 nm (I) 614.1 nm (II) 705.9 nm (I))

Sb

440 ± 80 220 ± 10

252.8 (I) 259.8 (I)

Cu

40 ± 6 20 ± 4

324.7 (I) 327.4 (I)

Al

50 ± 6 30 ± 2

309.3 (I) 396.2 (I)

Ca

0.05 ± 0.001 0.1 ± 0.01

393.4 (II) 422.6 (I)

Sr

0.1 ± 0.01 0.2 ± 0.01

407.7 (II) 421.5 (II)

Ti

16 ± 1 19 ± 1

334.9 (II) 376.1 (II)

Zn

20 ± 0.4 17 ± 1

334.5 (I) 481.0 (I)

Ba

Analyte

LOD (ng/μL)

Electrochemical Potential (V) Linear Range

R2 18

Pb Sb NG 2,4-DNT

0.30 ± 0.02 0.50 ± 0.03 0.10 ± 0.01 1.0 ± 0.03

(ng/μL) 0-15 0-5 0-60 0-50

-0.78 ± 0.02 -0.49 ± 0.01 +0.50 ± 0.005 +0.05 ± 0.1

0.999 0.991 0.999 0.999

Table 3. List of number of stubs per sample above positive threshold after LIBS analysis

SAMPLE ID 01A -Pt 02A-Pt 03A-Pt 04A-Pt 05 A-Pt 01 A-Rv 02A-Rv

Number of stubs 2 2 2 2 2 2 2

03A-Rv 04A-Rv 05A-Rv 01B-Pt 02B-Pt 03B-Pt 04B-Pt 05B-Pt 16B-Pt 17B-Pt 18B-Pt 101C-Pt 102C-Pt 103C-Pt 104C-Pt

2 2 2 4 4 4 4 4 4 4 4 4 4 4 4

Number of stubs per sample above positive threshold by LIBS (2-4 stubs per sample) Pb/Ba/ Pb/ Pb/ Sb/ only only Sb Ba Sb Ba Pb Ba none 1 1 1 1 1 1 1 1 1 1 1 1 1 1

2 4 2 2 1 2 1 1 1 1

1 1 1 2

1 1

Above positive threshold by EC (1 stub per sample) NG 2,4DNT + + + + + + + + + + +

1

2

+ +

+ +

2 3

+

2 3 3 1 3 3 3

2 1 1

+ + +

+

19

105C-Pt 106C-Pt 107C-Pt 108C-Pt 109C-Pt 110C-Pt Non shooters BKG 1-20

4 4 4 4 4 4

1 1

1 1 3 2 2

1 1

20

2 2 2

1

1 1

1

1

1

19

+ + + + + +

+

0

0

+ + +

Table 4. Reliability performance measure results and respective formulas.

Performance rate (%)

Formula [39]

LIBS

EC

LIBS + EC

False positive rate

Pr

5

0

0

r

25

43

4

True negative rate (Specificity)

T r

95

100

100

True positive rate (Sensitivity)

TPr

75

57

96

83

75

98

95

n.a

n.a

False negative rate

Accuracy A Likelihood ratio rate

LRr

20

Fig. 1. Left: Photograph of carbon conductive tab after LIBS analysis. Right: SEM image of the superficial damage on the adhesive.

21

Fig. 2. Identification of a characteristic GSR particle by SEM-EDS after screening of the same sample by LIBS and EC.

22

Sb 259.8 (I)

Pb 405.8 (I) Pb 368.3 (I)

Intensity a.u.

Intensity a.u.

Intensity a.u.

Sb 252.8 (I)

Wavelength (nm)

Intensity a.u.

Ba 455.4 (II)

Ba 553.4 (I) Intensity a.u.

Intensity a.u.

Ba 493.3 (II)

Ba 614.1 (II) Ba 705.9 (I)

Fig. 3. LIBS spectra from the stub collected from the hands of a shooter (center) and main emission lines for Sb, Pb and Ba (insets).

23

Fig. 4. LIBS signal for LIBS calibration curve for Barium (493.3nm) at different concentrations (top) and respective calibration curve (bottom).

24

Sb

Cu NG 2,4-DNT

WEC (Current A)

Pb

Potential applied (V)

Fig. 5. Identification of IGSR and OGSR using EC sensors from the hands of a shooter (same sample analyzed by LIBS as shown in Figure 3).

25

Sb SNR Pb SNR

500 120 100

Pb SNR

Sb SNR

Ba SNR

400

300

200

80 60 40

100

20

0

non shooter

0

shooter

non shooter

shooter Pb SNR

Sb40 SNR

50 Ba SNR

Pb SNR

Ba SNR

Sb SNR

100

20

0 0

non shooter

non shooter

shooter Ca

0

40

50

30 20

0

Non shooter

shooter

-10

10

5

10

0

Al

15

Al SNR

Si SNR

100

shooter

20

50

150

non shooter

Si

60

200

Ca SNR

shooter

0 Non shooter

shooter

Non shooter

shooter

Fig. 6. Box plot of the signal to noise ratio obtained by LIBS analysis on 112 samples. The central line in each box is the median, the edges of the box are the 25th and 75th percentiles, and the whiskers extend to the maximum and minimum data points not considered outliers. From top to bottom: a) box plots of Ba, Sb and Pb, b) box plots for Ba, Sb and Pb zoomed in the low ends of the shooter whiskers, c) box plot for Ca, Si and Al.

26

FORC 2017 122 

LIBS and Electrochemical methods provide practical, fast and reliable screening test for GSR detection



Notable advantage of the approach is the capability to conduct laboratory-based analysis and field detection of both inorganic and organic components.



Sampling and analytical scheme permits subsequent confirmatory analysis (SEM-EDS) on the same sample.

27

FAST screening Collection method

Carbon tape adhesive pads

LIBS

(e.g. Pb, Ba, Sb, Zn, Cu, C, N, O)

Laser beam hv

Sample surface

Sb

Sb

Pb

Ba

Electrochemical disposable sensors (e.g. Pb, Ba, Sb, Zn, DPA, DNT, N-DPA, EC)

Sb

Cu NG

Increased scientific validity

2,4-DNT

Pb Pb

Al

Ba Si Cu

Sb

Confirmation methods SEM-EDS

WEC (Current A)

Sr

Potential applied (V)