Characterization of the flowing afterglows of an N<sub>2</sub>–O<sub>2</sub>reduced-pressure discharge: setting the operating conditions to achieve a dominant late afterglow and correlating the NO<sub>β</sub>UV intensity variation with the N and O atom densities
Bibliographic record
Abstract
The flowing afterglow of an N 2 –O 2 discharge in the 0.6–10 Torr range is examined in the perspective of achieving sterilization of medical devices (MDs) under conditions ensuring maximum UV intensity with minimum damage to polymer-based MDs. The early afterglow is shown to be responsible for creating strong erosion damage, requiring that the sterilizer be operated in a dominant late-afterglow mode. These two types of afterglow can be characterized by optical emission spectroscopy: the early afterglow is distinguished by an intense emission from the 1st negative system (band head at 391.4 nm) while the late afterglow yields an overpopulation of the v ' = 11 ro–vibrational level of the N 2 ( B ) state, indicating a reduced contribution from the early afterglow N 2 metastable species. We have studied the influence of operating conditions (pressure, O 2 content in the N 2 –O 2 mixture, distance of the discharge from the entrance to the afterglow (sterilizer) chamber) in order to achieve a dominant late afterglow that also ensures maximum and almost uniform UV intensity in the sterilization chamber. As far as operating conditions are concerned, moving the plasma source sufficiently far from the chamber entrance is shown to be a practical means for significantly reducing the density of the characteristic species of the early afterglow. Using the NO titration method, we obtain the (absolute) densities of N and O atoms in the afterglow at the NO injection inlet, a few cm before the chamber entrance: the N atom density goes through a maximum at approximately 0.3–0.5% O 2 and then decreases, while the O atom density increases regularly with the O 2 percentage. The spatial variation of the N atom (relative) density in the chamber is obtained by recording the emission intensity from the 1st positive system at 580 nm: in the 2–5 Torr range, this density is quite uniform everywhere in the chamber. The (relative) densities of N and O atoms in the discharge are determined by using the actinometry method: the density of N atoms decreases from its maximum value at 0% O 2 as the percentage of O 2 is increased while the density of O atoms increases, almost linearly, as a function of the percentage of O 2 , as in the afterglow. The intensity variation of the NO β UV emission as a function of the percentage of O 2 is characterized by a maximum around 0.6% O 2 (2 Torr) followed by an approximately exponential decay. We observe that, in the 0–1% O 2 range, the UV emission is limited by the availability of O atoms. Beyond this point, the decrease of the UV intensity follows the decrease in the N atom density, while on the average, the O atom density keeps on increasing with O 2 %. Erosion of polymer microspheres is found to be strongest at the chamber axis when no O 2 is present, implying a dominant early afterglow. Adding even only 1% O 2 causes a strong quenching of the N 2 metastable species, leading to a dominant late afterglow and therefore considerably reducing the etching rate at the axis. In contrast, at 5 cm from the axis under the same operating conditions, a dominant late afterglow prevails; in the absence of oxygen, erosion is negligible, but it increases regularly as O 2 is introduced, following approximately the increase in the O atom density.
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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) | 0.000 | 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) | 0.002 | 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 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".