Isotropic and anisotropic metallic and bimetallic nanoparticles and their potential applications in biology
Bibliographic record
Abstract
The development of synthetic procedures that produce nanoscale materials with controlled morphology is a significant area of investigation in nanotechnology. We have developed new synthetic procedures for fabrication of isotropic and/or anisotropic nanomaterials composed of palladium, ruthenium, nickel and alloys of palladium-ruthenium. The nanomaterials were fully characterized and were found to display unique size dependent properties. The electrochemical properties of isotropic palladium, ruthenium and palladium-ruthenium nanoparticles were investigated and the results showed that the particles were capable of charge storage and charge transfer on demand. Anisotropic palladium, ruthenium and palladium ruthenium nanoparticles were also fabricated and fully characterized. The nanoparticles display unique magnetic properties. We further investigated the surface modification of inherent magnetic nanoparticles. The particles were found to have a strong affinity toward biological cells but lacked toxicity toward the cells. The work is effective toward developing new methods for using nanoparticles for cell targeting.
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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".