Optimization of Luminescent Metal-Organic Compounds for Oxygen Sensing Applications
Bibliographic record
Abstract
Oxygen sensing devices are valuable to several fields for medical, environmental, and pressure-sensing applications. Recent developments to optic fiber and waveguide technology have made luminescence-based molecular sensors more competitive than traditional sensing methods due to their easy modes of detection and portability. Several transition metal complexes have been investigated for their use as luminescent probes for the detection of molecular oxygen. Through studies that investigated their effectiveness in several different polymer matrices including polydimethylsiloxane (PDMS) and poly-(1-trimethylsilyl)-propyne (PTMSP), it was determined that compounds immobilized in PDMS were more stable while compounds immobilized in PTMSP were more sensitive. A more homogeneous dispersion was found to be achieved in PDMS compared to PTMSP, paving a path for potential sensing applications. This work provides the basis of a promising design of more robust oxygen sensors based on the incorporation of a more rigid ligand frame to stabilize metal complexes.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".