Oxidized Biochar as a Simple, Renewable Catalyst for the Production of Cyclic Carbonates from Carbon Dioxide and Epoxides
Bibliographic record
Abstract
Abstract Hard‐ and softwood residues (from birch and pine respectively) of forestry, pulp, and paper industries (e. g. sawdust, branches) were used to prepare biochar, which was then oxidized using nitric acid to produce catalytic carboxylic acid functionalized biochar. This oxidized biochar, ox – bc , in the presence of a co‐catalyst, showed excellent catalytic activity towards the cycloaddition reaction between CO 2 and epoxides using mild conditions (CO 2 pressure, 10 bar). No differences in catalytic activity were seen between the two types of oxidized biochar despite the hardwood ox – bc having a significantly higher surface area. The catalysts function through activation of the epoxide reagent via hydrogen‐bonding with carboxylic acid groups on the surface. The number of surface acid groups was reduced by reaction with 3‐aminopropyltriethoxysilane and the resulting material was inactive in the reactions studied. The ox – bc catalysts are sustainable, economic, and renewable alternatives for currently used heterogeneous systems and are also the first carbon‐based materials derived from biomass to exhibit good recyclability (over five runs) with a broad substrate scope for the production of cyclic carbonates from epoxides and CO 2 .
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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) | 0.000 | 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 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".