Catalytic Applications of Non‐Centrosymmetric Oxide Nanomaterials
Bibliographic record
Abstract
Noble-metal-free catalytic nanoparticles hold the promise being abundant, low-cost materials having a small environmental footprint and excellent performance, albeit inferior to that of noble metal counterparts. Several materials have a long-standing history of success in photocatalysis, in particular titanium dioxide, and in recent years more complex oxides and added functionality have emerged with enhanced performance. We will discuss different approaches related to the use of non-centrosymmetric and polar oxide nanoparticles and how the bulk photovoltaic effect, piezoelectricity, and pyroelectricity add to photocatalysis and tribocatalysis. We pay special attention to discriminate between the role of free versus that of bound charges within the catalyst, which is crucial to disentangle the different contributions to the catalytic reaction for the benefit of the overall enhanced catalytic performance in e.g. wastewater treatment and ultimately water-splitting.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".