Colorimetric indicators for volatile amines based on succinic anhydride (SAh)-grafted poly (lactic acid) (PLA)
Bibliographic record
Abstract
Smart materials that can undergo changes in color upon the detection of amines have the potential to provide information on the freshness of fish and meat. To engineer a material that undergoes a change in color upon exposure to biogenic amines, succinic anhydride functional groups - which are deprotonated in the presence of amines - are grafted onto a biopolymer poly(lactic acid) backbone. This material is then blended with a pH sensitive dye, yielding a material that shows a highly specific response to amines. In this system, the reaction between SAh and amines protonates the dye and leads to an irreversible change in color in the indicators. The resulting change in color was recorded and monitored with standardized photos and UV-Vis spectroscopy. Initially, indicators of different degrees of SAh (from 5 wt% to 45 wt%) grafted onto PLA were exposed to the vapours from a 400 ppm amine solution. The samples with higher degrees of grafting underwent the most visible changes in color. A more detailed study of the effect of temperature and amine concentration was performed on indicators with 30 wt% SAh. The limits of detection, half-time and kinetics of the response are also presented. Higher temperatures and concentrations were found to increase the degree of the color change while decreasing the half-time of the response of the indicators. This work shows potential opportunities for the development of simple real-time amine indicators.
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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 | 0.000 | 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 | 0.001 |
| 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".