Ecofriendly Route To Synthesize Nanomaterials for Biomedical Applications: Bioactive Polymers on Shape-Controlled Effects of Nanomaterials under Different Reaction Conditions
Bibliographic record
Abstract
Bioactive diethylaminoethyl dextran chloride (DEAE-D), a versatile polymer with numerous industrial applications, was used as a shape-directing agent for the synthesis of gold (Au) nanoparticles (NPs) in a typical green chemistry synthetic route. Shape-controlled growth was precisely directed by the quaternary amine functionalities of DEAE-D, while its polycationic nature provided simultaneous colloidal stabilization. Mechanistic aspects were drawn from different sets of reactions in which DEAE-D was directly used as a reducing agent with respect to reaction time and temperature. All reactions were simultaneously monitored with UV–visible studies, and NPs were characterized by TEM, SEM, and AFM analysis. Shape-controlled synthesis produced large extraordinarily thin microplates that were converted into small spherical NPs simply by switching the reaction to seed-growth (S-G) mode. DEAE-D-coated NPs thus produced were subjected to hemolysis for their possible use as drug release vehicles in systemic circulation so as to explore their possible biomedical applications.
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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 | 0.001 |
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".