Regulating the electronic state of Pt via architecting symbiotic oxide support for optimal alkaline hydrogen evolution reaction
Bibliographic record
Abstract
Optimization of the electronic structure of Pt δ+ 5 d orbitals by using a well–defined coordination environment to increase the efficiency of alkaline H 2 O dissociation kinetics remains challenging. Herein, TiO 2 quantum dots (QDs) were carefully introduced into a Pt/Co 3 O 4 system to form Pt/QDs/Co 3 O 4 , which created a pool of high–density Pt clusters anchored on an emerging symbiotic oxide surface. The strong interaction between QDs and Co 3 O 4 induced the redistribution of Pt 5 d orbital electrons. Spectroscopic characterization and theoretical calculations revealed that the resulting dual–active centers ( α –Pt–O–Co and β –Pt–O–Co) played a key role in balancing hydrogen adsorption and strengthening water dissociation. Therefore, the support effect of the symbiotic TiO 2 /Co 3 O 4 oxides resulted in the Pt/QDs/Co 3 O 4 catalyst having a mass activity 2.17 times higher than that of Pt/C at an overpotential of 200 mV. In addition, the Pt/QDs/Co 3 O 4 required only 1.78 V to reach an industrial–level current density of 500 mA cm −2 , and it achieved continuous robust operation for over 500 h in an anion exchange membrane water electrolyser. The results obtained after the extended synthesis of a Ru/QDs/Co 3 O 4 catalyst confirm the universality of the proposed support. This work sheds light on the surface activity of metals through an investigation of a support–facilitated design for efficient catalysts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".