Mechanochemical Transformations of Biomass into Functional Materials
Bibliographic record
Abstract
Biomass is one of the promising alternatives to petroleum-derived materials and plays a major role in our fight against climate change by providing renewable sources of chemicals and materials. Owing to its chemical and structural complexity, the transformation of biomass into value-added products requires a profound understanding of its composition at different scales and innovative methods such as combining physical and chemical processes. In this context, the use of mechanochemistry in biomass valorization is currently growing owing to its potentials as an efficient, sustainable, and environmentally friendly approach. This review highlights the latest advances in the transformation of biomass (i. e., chitin, cellulose, hemicellulose, lignin, and starch) to functional materials using mechanochemical-assisted methods. We focused here on the methodology of biomass processing, influencing factors, and resulting properties with an emphasis on achieving functional materials rather than breaking down the biopolymer chains into smaller molecules. Opportunities and limitations associated this methodology were discussed accordingly for future directions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 0.001 |
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".