A Comparison of Pd<sup>0</sup> Nanoparticles and Pd<sup>2+</sup> Modified Bi<sub>2</sub>O<sub>2</sub>CO<sub>3</sub> for Visible Light-Driven Photocatalysis
Bibliographic record
Abstract
As two effective approaches to increase the visible light-absorption capacities of photocatalysts, ion doping and metallic nanoparticles loading are compared in this work. Palladium was selected to modify Bi2O2CO3. Compared to dispersing palladium nanoparticles on the photocatalyst surface, it was more effective for the method of doping with palladium to shift the energy level within the bandgap of Bi2O2CO3 in improving its photocatalytic activity under visible light. This might be because doping with Pd2+ narrows the band gap of Bi2O2CO3 so as to increase the absorption capacity of visible light photons. Pd nanoparticles on the other hand can absorb photons to produce electrons which are then utilized by Bi2O2CO3 for photocatalytic reactions. Different mechanisms resulted in significant differences, and this work provides solid evidence that ion doping may be a more effective method to improve the photocatalytic activity of Bi2O2CO3.
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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".