Surface Modification of Detonation Nanodiamonds with Platinum and Palladium Nanoparticles
Bibliographic record
Abstract
Acetylacetonates of platinum group metals (M(acac)n, acac= CH3COCHCOCH3, n - oxidation state of metal) are the most suitable precursors for use in highly effective MOCVD (metal-organic chemical vapor deposition) processes because of their thermal properties, low price of initial ligand and accessible synthesis methods. In this study we have developed a simple, scalable inexpensive, MOCVD-like approach to the deposition of Pt and Pd nanoparticle dispersions on powder detonation nanodiamonds (DND) using combustion in air of powder mixtures of DND with Pt and Pd acetylacetonates. This one-step process requires no specialized apparatus, and is conducted at mild temperatures (180oC – 250oC). The substrate surface of DND initiates chemical thermal destruction of precursor and deposition of nanoparticle networks composed of constituent particles. DND-supported Pd and Pt nanoparticles with their loading being from 10 and 5wt. % were obtained the average of particle size 20-25 nm and 7-10nm decreases with decreasing the metal loading. For additional purification and disaggregation of the commercial detonation-synthesized nanodiamond (DNDcomm) the method of annealing of the powder mixtures DNDcomm with Na(acac) have been used. The purified diamond nanoparticulates (DND), as well as DNDcomm, Pt/DND and Pd/DND, were subjected to physicochemical characterizations, such as X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy dispersive X-ray (EDX) analysis.
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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 | 0.000 |
| 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) | 0.000 | 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".