Organic acids and protein compounds causing the photoluminescence properties of natural rubber membranes and the quenching phenomena from Au nanoparticle incorporation
Bibliographic record
Abstract
Natural rubber membranes were fabricated using latex from Hevea brasiliensis trees (clone RRIM 600) by casting, and controlling the time and temperature of thermal treatment. Three temperatures were used: 65, 80 and 120 °C and the corresponding annealing times of 6, 8, 10 and 12 h. The centrifugation of the latex produces the constituent phases: solid rubber (F1), serum or protein components (F2) and bottom fraction (F3). The photoluminescence properties could be correlated with organic acid components of latex. Natural rubber membranes were used as the active substrate (reducing agent) for the incorporation of colloidal Au nanoparticles synthesized by in situ reduction at different times. The intensity of photoluminescence bands assigned to the natural rubber decreases with the increase in amount of nanoparticles present on the membrane surface. It can be assumed that Au nanoparticles may be formed by reduction of the Au cation reacting with functional groups that are directly related to photoluminescence properties. However, the quenching of fluorescence may be attributed to the formation of a large amount of metal nanostructures on the natural rubber surface.
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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) | 0.001 | 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".