Impact of tensile and compressive forces on the hydrolysis of cellulose and chitin
Bibliographic record
Abstract
Mechanochemistry enables unique reaction pathways in comparison to conventional thermal reactions. Notably, it can achieve selective hydrolysis of cellulose and chitin, a set of abundant and recalcitrant biomass, by solvent-free ball-milling in the presence of acid catalysts. Although the merits of mechanochemistry for this reaction are known, the reaction mechanism is still unclear. Here, we show how the mechanical forces produced by ball-milling activate the glycosidic bonds of carbohydrate molecules towards hydrolysis. This work uses experimental and theoretical evaluations to clarify the mechanism. The experimental results reveal that the ball-mill accelerates the hydrolysis by mechanical forces rather than local heat. Meanwhile, the classical and quantum mechanics calculations indicate the subnano to nano Newton order of tensile and compressive forces that activate polysaccharide molecules in the ball-milling process. Although previous studies have taken into account only the stretching of the molecules, our results show that compressive forces are stronger and effective for the activation of glycosidic bonds. Accordingly, in addition to stretching, compression is crucial for the mechanocatalytic reaction. Our work connects the classical physics of ball-milling on a macro scale with molecular activation at a quantum level, which would help to understand and control mechanochemical reactions.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".