Excellent Low-Temperature Formaldehyde Decomposition Performance over Pt Nanoparticles Directly Loaded on Cellulose Triacetate
Bibliographic record
Abstract
Cellulose triacetate (CTA) was first applied as the catalytic support to load Pt nanoparticles for low-temperature formaldehyde (HCHO) decomposition. The room-temperature HCHO decomposition rate of the obtained catalyst (Pt/CTA) is 13.4 times and 4.3 times as high as that of the microcrystalline cellulose-supported Pt catalyst and Pt/TiO2 under the parallel preparation condition, respectively. With facile shaping, the CTA microsphere-supported Pt catalyst and the CTA film-supported Pt catalyst could also exhibit similar HCHO decomposition performance to that of the powdery one. Structural analyses showed that Pt nanoparticles (∼2.3 nm) could densely disperse on the small-area surface of Pt/CTA and provide abundant active sites. Moreover, only the HCHO molecules could slightly adsorb onto CTA, while other HCHO decomposition-related species absolutely could not. This is beneficial to the coordination of various steps of HCHO decomposition and the transfer of reaction species to vicinal active sites of Pt/CTA. HCHO-diffuse reflectance infrared Fourier transformed spectroscopy studies demonstrated that no species were accumulated on the Pt/CTA catalyst. Both the good Pt dispersion and unique adsorption properties of CTA were responsible for the excellent low-temperature HCHO decomposition performance of Pt/CTA.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".