In Situ Photo-Fenton-Like Tandem Reaction for Selective Gluconic Acid Production from Glucose Photo-Oxidation
Bibliographic record
Abstract
Biomass photorefining to selectively produce value-added bioproducts is an emerging alternative biomass valorization approach to alleviate energy crisis and achieve carbon neutrality. Here, we demonstrate an efficient and selective glucose photo-oxidation to gluconic acid via a rationally designed dual-functional carbon nitride photocatalyst that not only allows H 2 O 2 production via 2e – oxygen reduction reaction (2e-ORR) but also realizes in situ photo-Fenton-like reaction. As a result, the essential oxidative species ( • O 2 – and • OH) for glucose oxidation into gluconic acid are generated that achieves >60% glucose conversion and >60% of gluconic acid selectivity within 4 h. Density functional theory calculations demonstrate the superior performance of the photocatalyst for • O 2 – and H 2 O 2 generation. Further experimental results reveal that the moderate concentration of H 2 O 2 produced by 2e-ORR reaction plays a vital role in regulatinge gluconic acid selectivity. This work demonstrates a good example to realize selective biomass photorefining through tandem reaction of ORR and in situ photo-Fenton-like process, which could have profound impact on artificial photoenzyme systems involving moderate H 2 O 2 modulation.
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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".