Surface-Modified CeO<sub>2</sub>-Octahedron-Supported Pt Nanoparticles as Ethylene Scavengers for Fruit Preservation
Bibliographic record
Abstract
Catalytic oxidation of ethylene associated with the preservation of fruits and vegetables (F&V) at low temperatures remains challenging. To address this issue, CeO 2 -octahedron-supported Pt catalysts were synthesized and modified by capacitively coupled plasma for efficient catalytic oxidation of C 2 H 4 . After the plasma treatment, CeO 2 with rich oxygen vacancies was created, which acted as a support to facilitate the regulation of the size and dispersion of Pt nanoparticles. Compared with Pt/pristine CeO 2, the Pt/plasma-modified CeO 2 catalyst (Pt/CeO 2 -P) showed significantly higher reactivity. More than 99.9% of ethylene conversion induced by Pt/CeO 2 -P could be sustained longer than 50 h at 25 °C, and 30 min even at 0 °C. Thus, Pt/CeO 2 interface engineering by plasma modification technology is particularly promising for low-temperature catalytic oxidation of ethylene. Moreover, a comprehensive characterization was conducted to elucidate the reaction pathway and oxidation mechanism. From the preservation test using bananas as fruit samples, it was found that Pt/CeO 2 -P delayed postharvest deterioration and ripening of bananas due to the excellent ethylene scavenging effect created by the catalyst, thus demonstrating the great potential applications in F&V preservation.
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 | 0.000 |
| 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".