Metal-Free Sulfonate/Sulfate-Functionalized Carbon Nitride for Direct Conversion of Glucose to Levulinic Acid
Bibliographic record
Abstract
Metal-free heteroatom-doped carbonaceous materials such as carbon nitride (CN) with secondary/tertiary nitrogen-rich catalytic centers as well as chemical and thermal resilience can potentially serve as catalysts for many organic reactions. However, because of the stable alternate Csp 2 –Nsp 2 configuration of N-linked heptazine units (C 6 N 7 ), the chemical modification of CN via doping and functionalization has been a critical challenge. Herein, we report an exceptional 9.2% sulfur content in CN with sulfonate/sulfate functional groups (CNS) via a one-step in situ synthesis approach. When used as a catalyst for the dehydration/hydration of glucose, CNS catalysts demonstrate a relatively high yield and selectivity toward levulinic acid, LLA, (≈48% yield with 57% selectivity) production. CNS’s high activity of direct conversion of glucose to LLA can be attributed to the synergistic catalytic effects of multiple sulfur functionalities, better dispersibility, and microstructural porosity. The synthesized CNS catalysts offer an energy efficient direct LLA production route to bypass the multistep process of sugar to LLA conversion.
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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".