A microfabricated, low dark current a-Se detector for measurement of microplasma optical emission in the UV for possible use<i>on-site</i>
Bibliographic record
Abstract
Traditionally, samples are collected on-site (i.e., in the field) and are shipped to a lab for chemical analysis. An alternative is offered by using portable chemical analysis instruments that can be used on-site (i.e., in the field). Many analytical measurements by optical emission spectrometry require use of light-sources and of spectral lines that are in the Ultra-Violet (UV, ~200 nm – 400 nm wavelength) region of the spectrum. For such measurements, a portable, battery-operated, fiber-optic spectrometer equipped with an un-cooled, linear, solid-state detector may be used. To take full advantage of the advanced measurement capabilities offered by state-of-the-art solid-state detectors, cooling of the detector is required. But cooling and other thermal management hamper portability and use on-site because they add size and weight and they increase electrical power requirements. To address these considerations, an alternative was implemented, as described here. Specifically, a microfabricated solid-state detector for measurement of UV photons will be described. Unlike solid-state detectors developed on crystalline Silicon, this miniaturized and low-cost detector utilizes amorphous Selenium (a-Se) as its photosensitive material. Due to its low dark current, this detector does not require cooling, thus it is better suited for portable use and for chemical measurements on-site. In this paper, a microplasma will be used as a light-source of UV photons for the a-Se detector. For example, spectra acquired using a microplasma as a light-source will be compared with those obtained with a portable, fiber-optic spectrometer equipped with a Si-based 2080-element detector. And, analytical performance obtained by introducing ng-amounts of analytes into the microplasma will be described.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".