Floating Photothermal Hydrogen Production
Bibliographic record
Abstract
Solar-to-hydrogen (STH) is emerging as a promising approach for energy storage and conversion to contribute to carbon neutrality. The lack of efficient catalysts and sustainable reaction systems is stimulating the fast development of photothermal hydrogen production based on floating carriers to achieve unprecedented STH efficiency. This technology involves three major components: floating carriers with hierarchically porous structures, photothermal materials for solar-to-heat conversion and photocatalysts for hydrogen production. Under solar irradiation, the floating photothermal system realizes steam generation which quickly diffuses to the active site for sustainable hydrogen generation with the assistance of a hierarchically porous structure. Additionally, this technology is endowed with advantages in the high utilization of solar energy and catalyst retention, making it suitable for various scenarios, including domestic water supply, wastewater treatment, and desalination. A comprehensive overview of the photothermal hydrogen production system is present due to the economic feasibility for industrial application. The in-depth mechanism of a floating photothermal system, including the solar-to-heat effect, steam diffusion, and triple-phase interaction are highlighted by elucidating the logical relationship among buoyant carriers, photothermal materials, and catalysts for hydrogen production. Finally, the challenges and new opportunities facing current photothermal catalytic hydrogen production systems are analyzed.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".