Green Strategy Guided by Raman Spectroscopy for the Synthesis of Ammonium Carboxylated Nanocrystalline Cellulose and the Recovery of Byproducts
Bibliographic record
Abstract
A one-pot green procedure for the treatment of cellulosic biomass with ammonium persulfate (APS) was developed for the synthesis of highly crystalline carboxylated nanocrystalline cellulose (NCC–COOH), an emerging nanomaterial with a plethora of diversified applications. Raman spectroscopy proved applicable for monitoring the fate of APS and its two byproducts during the production of NCC–COOH from microcrystalline cellulose (MCC). The two main byproducts were then identified and quantified as ammonium sulfate (AS) and H 2 SO 4 with the latter accounted for 60% of the total sulfate ions in solution. On the basis of such findings, one-step neutralization of H 2 SO 4 and NCC with NH 4 OH immediately after reaction was implemented for the formation of additional AS, followed by its quantitative recovery by precipitation. This was a very effective and critical step in waste stream management and cost reduction for the large scale production of NCC. In addition, the process resulted in highly crystalline NCC with COO – NH 4 + groups, a nanomaterial with improved dispersion and thermal characteristics over NCC with COOH and COO – Na + groups.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".