Multi-species gas detection with long-wavelength VCSEL
Bibliographic record
Abstract
A long-wavelength VCSEL has been used for the first time for multi-species gas detection and for trace gas sensing. The VCSEL with a buried tunnel junction (VERTILAS, Germany) was capable of covering a spectral range of 7 nm or 28 cm<sup>-1</sup> (central wavelength at 1576.3 nm) with the laser temperature and injection current varied between 0-50 °C and 0.5-5 mA respectively. The pressure of CO:CO<sub>2</sub>=3:2 gas mixtures buffered with N<sub>2</sub> (N<sub>2</sub> content 0 - 90 %) was varied from 1 mBar up to 1 Bar. To avoid a non-linear dynamic tuning, the combination of a direct injection current with a saw-tooth waveform was used to sweep the laser frequency across absorption lines. A LabVIEW-based computer code was developed for multi-species gas analysis in time domain. Absorption spectra were averaged over 10<sup>2</sup>-10<sup>3</sup> laser scans. It has been shown that a cross interference from all collisional partners should be taken into account for accurate multi-component gas detection. A concentration of 600 ppm of CO<sub>2</sub> in atmospheric air (fractional absorption ~ 10<sup>-4</sup>) was detected with laser output power of 120 uW. Long-wavelength VCSELs can be used both for multi-species gas detection in a wide range of pressures and for trace gas monitoring.
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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 | 0.001 | 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".