Synthesis of Gold Nanoparticles Supported by Aggregated Assemblies of Triblock Copolymers in Aqueous Phase : Effect of Temperature
Bibliographic record
Abstract
The effect of temperature on the self-assembled behavior of polymers P103 and P84, and their subsequent use as soft templates for the synthesis of gold (Au) nanoparticles (NP) have been studied with the help of SEM, TEM, and UV-vis spectral measurements. Both the triblock copolymers (TBP) exist in the form of liquid crystalline thread like assemblies. P103 being more hydrophobic shows a structural transition from liquid crystal (LC) threads to sheets at 50°C and bear uniformly distributed Au NP, the size of which increases with the increase in temperature. P84 being more hydrophilic shows only LC threads and no sheets, but the LC threads bearing running groove at 50°C, act as wonderful nucleation sites for the growth of large cubic Au NP. The presence of surface cavities constituted by polyethylene oxide (PEO) and polypropylene oxide (PPO) blocks on LC phase of both TBPs are considered to be the nucleation sites for Au NP. The greater hydrophobicity of P103 in comparison to P84 favors the uniform distribution of NP throughout the LC phase while an increase in the temperature facilitates this process.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".