Enhanced nanoplasmonic heating in standoff sensing of explosive residues with infrared reflection-absorption spectroscopy
Bibliographic record
Abstract
Various standoff sensing techniques employing optical spectroscopy have been developed to address challenges in safely identifying trace amounts of explosives at a distance. A flexible anodic aluminum oxide (AAO) microcantilever and a high-power quantum cascade laser utilized as the infrared (IR) source are used for standoff IR reflection-absorption spectroscopy to detect explosive residues on a metal surface. Standoff sensing of trinitrotoluene (TNT) is demonstrated by exploiting the high thermomechanical sensitivity of a bimetallic AAO microcantilever. Moreover, sputtering gold onto the fabricated AAO nanowells generates a strong scattering and absorption of IR light in the wavelength range of 5.18 µm to 5.85 µm resulting in enhanced nanoplasmonic heating. Utilizing the IR absorption enhancement in this wavelength range, the plasmonic AAO cantilever could detect TNT molecules 7 times better than could the bimetallic AAO cantilever.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".