<sup>1</sup>H Spin–Lattice Relaxation Processes in Solutions of H<sub>2</sub>N–Fe<sub>3</sub>O<sub>4</sub> Nanoparticles: Insights from NMR Relaxometry
Bibliographic record
Abstract
1 H spin–lattice relaxation experiments have been performed for water and glycerol/water solutions of H 2 N–Fe 3 O 4 superparamagnetic nanoparticles (NPs) of about 7 nm diameter. The experiments encompass a broad frequency range covering 3 orders of magnitude, from 10 kHz to 10 MHz (referring to 1 H resonance frequency), and have been performed in the temperature range from 298 to 313 K, varying the concentration of the superparamagnetic species. This extensive dataset has been used for twofold purposes. The first one is to serve as a challenge for thorough tests of theoretical models describing nuclear relaxation in solutions of superparamagnetic NPs, depending on their magnetic properties and dynamics of the solvent molecules. The challenge is posed by the wish to reproduce the data in a broad range of magnetic fields (not only at high fields) and by the need to explain the differences in the relaxation scenarios for water and glycerol/water solutions by varying only the solvent parameters. The second purpose is to get insights into the magnetic properties (electronic relaxation properties) of the nanoparticles due to their high applicational potential.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".