Luminescence Quenching in Polymer/Filler Nanocomposite Films Used in Oxygen Sensors
Bibliographic record
Abstract
Luminescent oxygen sensors are devices in which the active element involves a luminescent dye in a polymer film. Oxygen partitions into the polymer from an adjacent gas or liquid phase and quenches the dye luminescence to an extent that depends on the amount of oxygen present in the film. When the dyes are dissolved in or attached to the molecules of a pure polymer film, the quenching kinetics can be described completely in terms of parameters that can be determined independently: the excited-state lifetime of the dye and the permeability ( P O 2 ) and diffusion coefficient ( D O 2 ) of oxygen in the polymer. In many sensors, nanometer-sized inorganic particles are often added to the active matrix. These particles are added either as carriers for the dye molecules or to reinforce the polymer film. The presence of these particles in the polymer complicates the quenching kinetics, because both the dyes and the oxygen molecules partition between the polymer matrix and the particle surfaces. The purpose of this article is to review the factors that operate to affect quenching kinetics in particle-filled polymer films. We provide a brief review of polymer composite systems used in sensors and a more detailed review of the factors that affect quenching kinetics in these systems. We end with a description of more sophisticated models that have been employed to analyze oxygen quenching of dyes adsorbed on the surface of inorganic particles in the hopes that similar models might be developed in the future to describe oxygen quenching in polymer composite films.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".