Core/shell 1T/2H-MoS2 nanoparticle induced synergistic effects for enhanced hydrogen evolution reaction
Bibliographic record
Abstract
This study investigates the photoelectrochemical potential of 1T/2H-MoS 2 nanoparticles synthesized via chemical vapor deposition. The 60 nm nanoparticles, analyzed using SEM, XRD, Raman spectroscopy, and XPS, have a high-quality mixed-phase composition. TEM revealed a core–shell structure. A MoS 2 /p-Si photocathode showed a current density of −13.5 ± 1 mA/cm 2 at 0 V and an onset potential of 110 mV, with rapid photoresponse times and an 8 % IPCE at 450 nm. The mixed-phase and core–shell structure enhance electronic and catalytic properties, promising advancements in renewable energy technologies. Green hydrogen is a highly sought-after clean fuel for the next generation of engines aimed at achieving net-zero emissions. Herein, we design and fabricate a mixed-phase core/shell nanoparticles consisting of a semiconducting 2H-MoS 2 core and a metallic 1T-MoS 2 coating. The core/shell exhibits spherical morphology with an average diameter of 60 nm. To leverage this unique structure, we develop a photocathode device composed of 1T/2H-MoS 2 core/shell integrated with p-type silicon to catalyze hydrogen evolution reaction via water splitting driven by solar energy. The core/shell device demonstrates, at zero bias, a remarkable current density of −13.5 ± 1 mA/cm 2 and an onset potential of 110 mV. Additionally, the device exhibited a rapid photoresponse time and a high incident photon-to-current efficiency reaching 80 % at 450 nm. Our findings highlight the synergistic effect of 1T/2H-MoS 2 mixed-phase core/shell structure in developing the next generation of high-efficient photocatalysts for green hydrogen generation.
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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".