pH and thermo-responsive tetronic micelles for the synthesis of gold nanoparticles: effect of physiochemical aspects of tetronics
Bibliographic record
Abstract
Micelles of the star shaped block polymers "tetronics" were employed for the synthesis of gold (Au) nanoparticles (NPs) under the effect of pH and temperature variation. The presence of the diamine core in the tetronic macromolecule made its micelles highly pH responsive, thereby dramatically altering the physiochemical properties. Likewise, a high degree of hydration made the micelles temperature sensitive. UV-visible studies, transmission electron microscopy (TEM), gel electrophoresis, and structure optimization by energy minimization were applied to understand the physiochemical aspects of tetronic micelles and their further role in the synthesis of Au NPs. Synthesis of Au NPs was triggered by the surface cavities of the micelles and hence the NPs simultaneously adsorbed on the micelle surface. Low pH induced high hydration and temperature responsive well defined vesicular morphologies bearing Au NPs, while high pH produced mainly large and compact compound micelles carrying NPs. Both pH and temperature responsive behaviors of different tetronics significantly influenced the synthesis of Au NPs and thus demonstrated their ability to act as nanoreactors for the materials synthesis under different experimental conditions.
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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".