The effect of temperature and freeze–thaw processes on gold nanorods
Bibliographic record
Abstract
An application of increasing importance is the use of gold nanorods (AuNRs) as nanosensors and nanoprobes. We explored the possibility of using AuNRs as detectors for various temperature exposures. We measured the effects of freeze-thaw processes on AuNRs in aqueous solution by visual inspection (thermochromism), transmission electron microscopy (TEM; morphological reshaping and aggregation), and absorbance spectroscopy (plasmon peak shifts). TEM images revealed that AuNRs coalesced after prolonged exposures to -20 degrees C. The results suggest that solute rejection and cetyltrimethylammonium bromide (CTAB) bilayer crystallization underlie the mechanism of AuNR aggregation during freezing. This non-reversible aggregation appears to be unique to CTAB-protected AuNRs. Due to their unique freezing properties, we propose that AuNRs may have utility as freeze-thaw temperature nanoprobes.
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 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 | 0.000 | 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) | 0.000 | 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".