pH Responsive Bioactive Lead Sulfide Nanomaterials: Protein Induced Morphology Control, Bioapplicability, and Bioextraction of Nanomaterials
Bibliographic record
Abstract
Precise morphologies of pH responsive bioactive lead sulfide nanoparticles (PbS NPs) were synthesized by using industrially and environmentally important proteins like zein and lysozyme (Lys), and a bioactive polymer diethylaminoethyl dextran chloride (DEAE). Though, proteins are not known morphology control agents, zein demonstrated a fine crystal growth control of PbS NPs better than Lys as well as DEAE, and even better than conventional surfactants known for their shape control behavior. Proteins and DEAE coated NPs thus obtained were highly pH responsive in terms of a color change from light gray (at low pH) to dark brown (at high pH). Bioapplicability of coated NPs was done by subjecting them to hemolysis. Both Lys and DEAE coated NPs did not induce any significant hemolysis and demonstrated their good compatibility and usability in systemic circulation. For their industrial scale uses, different extraction methods were proposed by using other industrially important biomolecules and ionic liquids. Alginic acid and xanthan gum were excellent complexing agents for an instant extraction of Lys and DEAE coated NPs from aqueous phase. Ionic liquid exhibited excellent extraction ability in both organic as well as aqueous phases.
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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 | 0.001 | 0.001 |
| 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) | 0.000 | 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".