Alternating magnetic field heat behaviors of PVDF fibrous mats filled with iron oxide nanoparticles
Bibliographic record
Abstract
To study the magnetic heat behaviors, iron oxide nanoparticles (IONPs) and the polyvinylidene fluoride (PVDF) fibrous mats filled with IONPs were prepared by using coprecipitaion method and the electrospinning technique. The synthesized IONPs exhibited a magnetization of about 72 emu/g with average diameter of about 10 nm. The magnetizations of PVDF fibrous mats filled with IONPs showed 2.6 emu/g, 5.5 emu/g and 9.9 emu/g for 5 wt.%, 10 wt.% and 20 wt.% IONPs concentration, respectively. The heat of the magnetic fibrous mats were measured under various alternating magnetic fields (90, 128, and 167 Oe), frequencies (190, 250 and 355 kHz). The maximum saturated temperature showed up to 62 °C for 20 wt.% IONPs filled in PVDF fibrous mat under 167 Oe and 355 kHz.
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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) | 0.001 | 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".