High Yield Synthesis and Application of Magnetite Nanoparticles (Fe3O4)
Bibliographic record
Abstract
Magnetite nanoparticles (Fe3O4), average particle size of 12.9 nm, were synthesized de novo from ferrous and ferric iron salt solutions (total iron salt concentration of 3.8 mM) using steady-state headspace NH3(g), 3.3% v/v, at room temperature and pressure, without mechanical agitation, resulting in >99.9% yield. Nanoparticles size distributions were based on enumeration of TEM images and chemical compositions analyzed by: XRD, EDXRF, and FT-IR; super-paramagnetic properties were analyzed by magnetization saturation (74 emu/g). Studies included varying headspace [NH3(g)] (1.6, 3.3, 8.4% v/v), and total iron concentrations (1.0 mM, 3.8 mM, 10.0 mM, and >>10 mM). An application of the unmodified synthesized magnetite nanoparticles included analyses of tetracycline’s (50, 100, 200, 300, and 400 ppb) in aqueous, which was compared to the same tetracycline concentrations prepared in aqueous synthesis suspension with >97% extraction, analyzed with LC-MS/MS.
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 | 0.001 |
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".