Switchable CO2 electroreduction via engineering active phases of Pd nanoparticles
Bibliographic record
Abstract
Active-phase engineering is regularly utilized to tune the selectivity of metal nanoparticles (NPs) in heterogeneous catalysis. However, the lack of understanding of the active phase in electrocatalysis has hampered the development of efficient catalysts for CO2 electroreduction. Herein, we report the systematic engineering of active phases of Pd NPs, which are exploited to select reaction pathways for CO2 electroreduction. In situ X-ray absorption spectroscopy, in situ attenuated total reflection-infrared spectroscopy, and density functional theory calculations suggest that the formation of a hydrogen-adsorbed Pd surface on a mixture of the α- and β-phases of a palladium-hydride core (α+β PdH x @PdH x ) above −0.2 V (vs. a reversible hydrogen electrode) facilitates formate production via the HCOO* intermediate, whereas the formation of a metallic Pd surface on the β-phase Pd hydride core (β PdH x @Pd) below −0.5 V promotes CO production via the COOH* intermediate. The main product, which is either formate or CO, can be selectively produced with high Faradaic efficiencies (>90%) and mass activities in the potential window of 0.05 to −0.9 V with scalable application demonstration.
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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) | 0.000 | 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".