Standoff Mechanical Resonance Spectroscopy Based on Infrared-Sensitive Hydrogel Microcantilevers
Bibliographic record
Abstract
This paper reports a highly sensitive and selective remote chemical sensing platform for surface-adsorbed trace chemicals by using infrared (IR)-sensitive hydrogel microcantilevers. Poly(ethylene glycol) diacrylate (PEG-DA) hydrogel microcantilevers are fabricated by ultraviolet (UV) curing of PEG-DA prepolymer introduced into a poly(dimethylsiloxane) mold. The resonance frequency of a PEG-DA microcantilever exhibits high thermal sensitivity due to IR irradiation/absorption. When a tunable IR laser beam is reflected off a surface coated with target chemical onto a PEG-DA microcantilever, the resonance frequency of the cantilever shifts in proportion to the chemical nature of the target molecules. Dynamic responses of the PEG-DA microcantilever can be obtained in a range of IR wavelengths using a tunable quantum cascade laser that can form the basis for the standoff mechanical resonance spectroscopy (SMRS). Using this SMRS technique, we have selectively detected three compounds, dimethyl methyl phosphonate (DMMP), cyclotrimethylene trinitramine (RDX), and pentaerythritol tetranitrate (PETN), located 4 m away from the PEG-DA microcantilever detector. The experimentally measured limit of detection for PETN trace using the PEG-DA microcantilever was 40 ng/cm 2 . Overall, the PEG-DA microcantilever is a promising candidate for further exploration and optimization of standoff detection methods.
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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) | 0.004 | 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".