Sustainable catalytic pathways for biofuel precursors: quantitative conversion of glucose to gluconic acid using Pt-Zn biochar catalyst
Bibliographic record
Abstract
Achieving quantitative conversion of biomass-derived feedstocks under ambient environmental conditions (20°C, atmospheric air, 0.1 MPa) is a critical milestone for sustainability in chemical processes. Herein, the quantitative conversion of glucose to gluconic acid was accomplished under ambient environmental conditions without any additives using a Pt-Zn intermetallic nanoparticle-supported biochar catalyst prepared from raw rice straw (Pt-Zn/strawC) via a straightforward one-pot solvothermal reaction with ethylene glycol solvent. Spectroscopic analyses verified the formation of the Pt-Zn intermetallic alloy and confirmed strong electronic metal-support interactions. The Pt-Zn/strawC catalyst (Pt:Zn molar ratio of 1:6) was highly selective for the conversion of glucose to gluconic acid, whereas yields as high as 99.9% (98.9% gluconic acid, 1.0% glucaric acid) were reached at 20 oC under base-free and additive-free conditions. Isotope measurements and density functional theory revealed synergistic interactions in the Pt-Zn alloy, wherein the alloy tended to absorb glucose and active O2 into superoxide radical (O2·). This work demonstrates a chemocatalytic method that is practical for environmental conditions and provides a new avenue for sustainable conversion of lignocellulosic biomass to chemical 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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".