Paramagnetic Nanocrystals: Remarkable Lanthanide-Doped Nanoparticles with Varied Shape, Size, and Composition
Bibliographic record
Abstract
Magnetic nanoparticles have been developed in recent years with applications in unique and crucial areas such as biomedicine, data storage, environmental remediation, catalysis, and so forth. NaYF4 nanoparticles were synthesized and isolated with lanthanide dopant percentages, confirmed by ICP-OES measurements, of Er, Yb, Tb, Gd, and Dy that were in agreement with the targeted ratios. SEM images showed a distinct variation in particle size and shape with dopant type and percentage. HRTEM and XRD studies confirmed the particles to be crystalline, possessing both α and β phases. Magnetic measurements determined that all of the nanoparticles were paramagnetic and did not exhibit a blocking temperature from 2 to 300 K. The multifunctional properties of these nanoparticles make them suitable for many applications, such as multimodal imaging probes, up-conversion fluorescent markers, as well as MRI contrast agents.
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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) | 0.000 | 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 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".