Interfacial Electronic Modulation of Dual-Monodispersed Pt–Ni3S2 as Efficacious Bi-Functional Electrocatalysts for Concurrent H2 Evolution and Methanol Selective Oxidation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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 CO 2 emission. Herein, the hetero-nanocrystals between monodispersed Pt (~ 2 nm) and Ni 3 S 2 (~ 9.6 nm) are constructed as active electrocatalysts through interfacial electronic modulation, which exhibit superior bi-functional activities for methanol selective oxidation and H 2 generation. The experimental and theoretical studies reveal that the asymmetrical charge distribution at Pt–Ni 3 S 2 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 CH 3 OH 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 CO 2 emission. Meanwhile, the Pt–Ni 3 S 2 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.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 it