Visible‐Light‐Driven Lignin Valorization into Value‐Added Chemicals and Sustainable Hydrogen Using Zn<sub>1‐<i>x</i></sub>Cd<sub><i>x</i></sub>S Solid Solutions as Photocatalyst
Bibliographic record
Abstract
Abstract Biomass photorefinery for simultaneous production of value‐added chemicals and sustainable hydrogen holds promising perspective to achieve a negative carbon economy. However, insight into lignin valorization by the photorefinery approach is still lacking due to the extremely complex structure and component. In this work, we design a series of Zn 1‐ x Cd x S solid solutions as photocatalyst to reveal the photocatalytic mechanism for model component conversion. Bandgap engineering by changing the Zn/Cd ratio is proven to efficiently regulate the reaction pathway. Specifically, Zn 0.75 Cd 0.25 S (ZCS25) presented the best performance for hydrogen evolution (610±105 μmol h −1 g cat. −1 ) while Zn 0.5 Cd 0.5 S (ZCS50) demonstrated the best substrate conversion to monophenolic compounds. Besides, the well‐designed Zn 1‐x Cd x S solid solutions also show the ability to produce hydrogen and eliminate a methoxy group from real lignin by the photorefinery approach. This present work demonstrates a good example of biomass valorization by careful design of photocatalysts.
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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".