Scalable Synthesis of Hollow MoS <sub>2</sub> Nanoparticles Modified on Porous Ni for Improved Hydrogen Evolution Reaction
Bibliographic record
Abstract
Developing an inexpensive non-noble metal catalyst is essential in the electrochemical water reduction. However, to choose the support for hydrogen-producing catalyst is still a problem that needs to be solved. Herein, we report a novel route combining powder metallurgy and hydrothermal synthesis to fabricate Ni/MoS 2 catalysts for boosting the hydrogen evolution reaction performance. Powder metallurgy produces the suborbicular pores on the surface and inside Ni once the sintering temperature reaches 1000 °C. The hollow MoS 2 nanoparticles are successfully modified on the surface of porous Ni by hydrothermal synthesis. The hollow structure of MoS 2 nanoparticles provides more active sites for electrochemical reaction and the porous Ni matrix with the porosity of 16.5% exhibits higher electronic conductivity, which endows the Ni/MoS 2 −1000 catalyst with an excellent hydrogen evolution reaction activity. The Ni/MoS 2 −1000 shows a low overpotential of 229 mV at the current densities of 10 mA·cm −2 with a small Tafel slope of 76 mV·dec −1 . This study provides guidelines on the large-scale synthesis of nanostructured electrocatalysts with porous Ni as the support.
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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".