Floating Carbon Nitride Composites for Practical Solar Reforming of Pre‐Treated Wastes to Hydrogen Gas
Bibliographic record
Abstract
Abstract Solar reforming (SR) is a promising green‐energy technology that can use sunlight to mitigate biomass and plastic waste while producing hydrogen gas at ambient pressure and temperature. However, practical challenges, including photocatalyst lifetime, recyclability, and low production rates in turbid waste suspensions, limit SR's industrial potential. By immobilizing SR catalyst materials (carbon nitride/platinum; CN x |Pt and carbon nitride/nickel phosphide; CN x |Ni 2 P) on hollow glass microspheres (HGM), which act as floating supports enabling practical composite recycling, such limitations can be overcome. Substrates derived from plastic and biomass, including poly(ethylene terephthalate) (PET) and cellulose, are reformed by floating SR composites, which are reused for up to ten consecutive cycles under realistic, vertical simulated solar irradiation (AM1.5G), reaching activities of 1333 ± 240 µmol H2 m −2 h −1 on pre‐treated PET. Floating SR composites are also advantageous in realistic waste where turbidity prevents light absorption by non‐floating catalyst powders, achieving 338.1 ± 1.1 µmol H2 m −2 h −1 using floating CN x versus non‐detectable H 2 production with non‐floating CN x and a pre‐treated PET bottle as substrate. Low Pt loadings (0.033 ± 0.0013% m/m) demonstrate consistent performance and recyclability, allowing efficient use of precious metals for SR hydrogen production from waste substrates at large areal scale (217 cm 2 ), taking an important step toward practical SR implementation.
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How this classification was reachedexpand
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".