Highly Dispersed Ni Atoms and O<sub>3</sub> Promote Room-Temperature Catalytic Oxidation
Bibliographic record
Abstract
Transition metal oxides are promising catalysts for catalytic oxidation reactions but are hampered by low room-temperature activities. Such low activities are normally caused by sparse reactive sites and insufficient capacity for molecular oxygen (O 2 ) activation. Here, we present a dual-stimulation strategy to tackle these two issues. Specifically, we import highly dispersed nickel (Ni) atoms onto MnO 2 to enrich its oxygen vacancies (reactive sites). Then, we use molecular ozone (O 3 ) with a lower activation energy as an oxidant instead of molecular O 2 . With such dual stimulations, the constructed O 3 –Ni/MnO 2 catalytic system shows boosted room-temperature activity for toluene oxidation with a toluene conversion of up to 98%, compared with the O 3 –MnO 2 (Ni-free) system with only 50% conversion and the inactive O 2 –Ni/MnO 2 (O 3 -free) system. This leap realizes efficient room-temperature catalytic oxidation of transition metal oxides, which is constantly pursued but has always been difficult to truly achieve.
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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".