Laser‐induced breakdown spectroscopy/laser ablation coupled to inductively coupled plasma mass spectrometry (<scp>LIBS</scp>/<scp>LA</scp>‐<scp>ICPMS</scp>) for the forensic screening and discrimination of lead‐free solders
Bibliographic record
Abstract
The tandem LIBS/LA-ICPMS technique is a desirable tool for the multi-elemental determination, characterization, and classification of alloys as forensic evidence. In this study, LIBS/LA-ICPMS is validated for the forensic evaluation of lead-free solder alloys, which form valuable evidence from post-blast crime scenes involving homemade and improvised explosive devices. LIBS/LA-ICPMS is competitive with other spectroscopic-based forensic techniques as it is in situ, analyzes samples directly, and requires minimal destruction of the exhibit. Following a one-standard calibration technique, nine major (alloying metals) and trace elements (impurities or additives) are quantified in lead-free solders. Optimizing laser parameters and using Pb as a naturally occurring internal standard are shown to compensate for mass-dependent drift and matrix effects. The quantitative results of Pb-free certified reference materials align with certificate values and with results from two techniques in a cross-validation comparison, including electrothermal vaporization-inductively coupled plasma optical emission spectrometry and neutron activation analysis. Utilizing peak ratios in a model of principal component analysis is presented to identify key compositional differences among solders and provide a visual model for solder discrimination. Outcomes of this approach demonstrate the potential for associating or discriminating lead-free solders, including different solders from the same manufacturer. Together, this technique can establish chemical concordance among known and questioned materials and offers a utilitarian approach for the forensic assessment of trace evidence.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".