Nanocomposites of nanocrystalline cellulose for enzyme immobilization
Bibliographic record
Abstract
We describe the synthesis, characterization and use of a composite material made of a renewable source and metallic nanoparticles for biosensing applications. Nanocrystalline cellulose (NCC) is a product isolated from natural cellulose fibers, which is of approximately 100 nm long and 10 nm wide in size. We augmented the surface area and tailored the chemical affinity of NCC by optimally dressing it with gold nanoparticles (AuNPs). The deposition of AuNPs on NCC was controlled by using cationic polyethylenimine (PEI) at different pHs. AuNPs were thiol-functionalized using different linkers prior to enzyme immobilization. The enzyme (glucose oxidase or GOx) was conjugated on the composite by carbodiimide coupling, and subsequent activation of linker-carboxylic acid group. Our results showed that GOx was attached to the surface of the NCC nanocomposite. Moreover, the amount of GOx loaded onto the support depended on the length of the thiol-linker used. The lower value (20.3 mg/mg of support) was obtained with the longer thiol-linker (11 carbon chain) compared to 25.2 mg/mg of support for the smaller thiol-linker (3 carbon chain).
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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) | 0.001 | 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".