Electrocatalytic Glucose Upgrading by Sulfonated Carbon for Sustainable Manufacturing
Bibliographic record
Abstract
Abstract In a sustainable economy, manufacturing is based on renewable raw materials like biomass instead of nonrenewable ones like petroleum. This work is a step toward that goal: we studied the transformation of glucose into industrial raw materials through electro‐oxidation with sulfonated carbon catalyst. Sulfonated carbon has been used as a thermocatalyst for glucose conversion, but until now it has not been used as an electrocatalyst. We identified nine products (oxalic acid, gluconic acid, tartaric acid, maleic acid, glycolic acid, arabinose, formic acid, acetic acid, and 5‐hydroxymethylfurfural), whereas glucose electrocatalysis yields that were published by others report five products or less. The optimal conditions in our experiments are a sulfonated carbon catalyst at + 1.5 V versus Ag/AgCl of applied potential and 2 h of oxidation time in 0.5 M K 2 CO 3 electrolyte. At that condition, the product yields are 16.3% for formic acid, 5.8% for acetic acid, 4.9% for glycolic acid, 4.6% for 5‐hydroxymethylfurfural, 1.6% for oxalic acid, 1.5% for tartaric acid, 1.4% for arabinose, and 1.1% for gluconic acid, for a total of 37.2% for the identified products. The next step is to explore whether sulfonated carbon electro‐oxidation can convert cellulose (a polymer of glucose) into those identified products.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".