Liquid and gas mid-infrared integrated spectroscopic sensor
Bibliographic record
Abstract
Mid-infrared (mid-IR) waveguide sensors were fabricated using two platforms: chalcogenide glasses (ChGs) and porous silicon (PSi). ChGs layers were deposited through RF magnetron sputtering while PSi layers were prepared by electrochemical anodization. Ridge waveguides were patterned using standard i-line photolithography and reactive ion etching for both platforms. The ChGs waveguides exhibit a wide transparency range from λ = 3.94 to 8.95 µm, with a minimum propagation losses value of 2.5 dB/cm at λ = 7.58 µm, while PSi transparency range is from λ = 3.94 to 4.55 µm with a minimum propagation losses value of 9.1 dB/cm at λ = 4.12 µm. To validate the proposed ChGs sensor, a spectroscopic liquid sensing experiment was performed using acetonitrile and isopropanol. The results showed an estimated limit of detection (LoD) of 610 ppm at λ = 4.44 µm for acetonitrile and a LoD of 300 ppm at λ = 7.25 µm for isopropanol, enabled by the evanescent field interaction. Regarding gas sensing, CO 2 was used as the analyte. A LoD of 17000 ppm at λ = 4.28 µm was achieved using the ChGs platform. The sensing application was improved with the PSi platform. Due to the open pores, light and gas molecules interact within the internal volume, unlike the ChGs platform, where the interaction occurs with the evanescent part of the light. This results in an exalted external confinement factor, Γ, over 75 times greater for the PSi platform, achieving a LoD of 600 ppm at λ = 4.26 µm for CO 2 sensing. Estimation of concentrations from mixtures of two solutions through deconvolution of the measured spectra was also achieved with good approximations, validating the transduction capabilities in a complex environment using the ChGs platform.
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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".