Interfacial Electronic Modulation of Dual-Monodispersed Pt–Ni3S2 as Efficacious Bi-Functional Electrocatalysts for Concurrent H2 Evolution and Methanol Selective Oxidation
Bibliographic record
Abstract
Abstract Constructing the efficacious and applicable bi-functional electrocatalysts and establishing out the mechanisms of organic electro-oxidation by replacing anodic oxygen evolution reaction (OER) are critical to the development of electrochemically-driven technologies for efficient hydrogen production and avoid CO2 emission. Herein, the hetero-nanocrystals between monodispersed Pt (~ 2 nm) and Ni3S2 (~ 9.6 nm) are constructed as active electrocatalysts through interfacial electronic modulation, which exhibit superior bi-functional activities for methanol selective oxidation and H2 generation. The experimental and theoretical studies reveal that the asymmetrical charge distribution at Pt–Ni3S2 could be modulated by the electronic interaction at the interface of dual-monodispersed heterojunctions, which thus promote the adsorption/desorption of the chemical intermediates at the interface. As a result, the selective conversion from CH3OH to formate is accomplished at very low potentials (1.45 V) to attain 100 mA cm−2 with high electronic utilization rate (~ 98%) and without CO2 emission. Meanwhile, the Pt–Ni3S2 can simultaneously exhibit a broad potential window with outstanding stability and large current densities for hydrogen evolution reaction (HER) at the cathode. Further, the excellent bi-functional performance is also indicated in the coupled methanol oxidation reaction (MOR)//HER reactor by only requiring a cell voltage of 1.60 V to achieve a current density of 50 mA cm−2 with good reusability.
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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".