Engineered Electronic States of Transition Metal Doped TiO<sub>2</sub> Nanocrystals for Low Overpotential Oxygen Evolution Reaction
Bibliographic record
Abstract
Electrochemical oxygen evolution reaction (OER) involves high overpotential at the oxygen evolving electrode and thereby suffers significant energy loss in the proton exchange membrane water electrolyzer. To reduce the OER overpotential, precious ruthenium and iridium oxides are most commonly used as anode electrocatalyst. Here we report marked reduction in overpotential for the OER using transition metal (TM) doped TiO 2 nanocrystals (NCs). This reduction in overpotential is attributed to d-orbitals splitting of the doped TMs in the TM-doped TiO 2 NCs and their interactions with the oxyradicals (intermediates of OER) facilitating the OER. The d-orbital spitting of TMs in TM-doped TiO 2 NCs is evident from the change in original pearl white color of undoped TiO 2 NCs and UV–vis absorption spectra.
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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".