Hydrolyzed Forms of Cellulose and Its Metal Composites for Hydrogen Generation: An Experimental and Theoretical Investigation
Bibliographic record
Abstract
The quest for a smooth transition from fossil fuels to clean and sustainable energy has warranted studies on alternative energy materials. Herein, we report on an experimental and theoretical study focused on hydrogen generation through the hydrolysis of microcrystalline cellulose (MCC) treated in different media (deionized water, sodium hydroxide) and MCC functionalized with magnesium (MCC-Mg), titanium (MCC-Ti), and niobium (MCC-Nb). The XRD results reveal the decreased crystallinity of MCC due to ball milling along with the formation of metal oxide composites between MCC and various metals (magnesium, titanium, and niobium). Theoretical studies using NVT molecular dynamic simulations with the NH chain thermostat implemented in the Dmol3 provides further support to the experimental results reported herein. The results from the experimental and theoretical studies revealed that ball milling and composite formation with metal species enhanced the kinetics of the hydrolysis of MCC and, consequently, hydrogen generation, while the addition of NaOH and urea inhibited the hydrogen yield.
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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) | 0.002 | 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".