Comparison of structure and magnetic properties of Mn–Zn ferrite mechanochemically synthesized under argon and oxygen atmospheres
Bibliographic record
Abstract
Nanocrystalline Mn0.5Zn0.5Fe2O4 ferrite was successfully synthesized by ball milling a powder mixture of MnO, ZnO, and Fe2O3 under argon and oxygen atmospheres. The effects of the milling time, milling atmosphere, and annealing temperature on the milled powders were examined. X-ray diffractometry (XRD), scanning electron microscopy, and transmission electron microscopy were used to evaluate the powder particle structure. The XRD results indicated that after 20 h of ball milling the MnO–ZnO–Fe2O3 powder reacted with a solid-state diffusion reaction route producing Mn–Zn ferrite nanoparticles in the milled samples with both atmospheres. However, some Fe3O4 phase alongside Mn–Zn ferrite, both being spinel-phase, was detected for 40 h milled powders in the argon atmosphere. Those milled powders in the argon atmosphere had smaller crystallite size than the other ones. In the final stage of milling (40 h), the average crystallite size and lattice strain were 20 nm and 0.51%, respectively, ans 25 nm and 0.48% for milled samples in the argon and oxygen atmospheres, respectively. Vibrating sample magnetometer results indicate that the saturation magnetization and coercivity were 34 emu/g and 30 Oe, 18 emu/g and 70 Oe, respectively, for the 40 h milled samples in argon and oxygen, which were annealed at 800 °C for 2 h.
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) | 0.000 | 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".