Temperature dependence on the mass susceptibility and mass magnetization of superparamagnetic Mn–Zn–ferrite nanoparticles as contrast agents for magnetic imaging of oil and gas reservoirs
Bibliographic record
Abstract
The mass susceptibility (χmass) and mass magnetization (Mmass) were determined for a series of ternary manganese and zinc ferrite nanoparticles (Mn–Zn ferrite NPs, MnxZn1−xFe2O4) with different Mn:Zn ratios (0.08 ≤ x ≤ 4.67), prepared by the thermal decomposition reaction of the appropriate metal acetylacetonate complexes, and for the binary homologs (MxFe3−xO4, where M = Mn or Zn). Alteration of the Mn:Zn ratio in Mn–Zn ferrite NPs does not significantly affect the particle size. At room temperature and low applied field strength the mass susceptibility increases sharply as the Mn:Zn ratio increases, but above a ratio of 0.4 further increase in the amount of manganese results in the mass susceptibility decreasing slightly, reaching a plateau above Mn:Zn ≈ 2. The compositional dependence of the mass magnetization shows less of a variation at room temperature and high applied fields. The temperature dependence of the mass magnetization of Mn–Zn ferrite NPs is significantly less for Mn-rich compositions making them more suitable for downhole imaging at higher temperatures (>100 °C). For non-shale reservoirs, replacement of nMag by Mn-rich Mn–Zn ferrites will allow for significant signal-to-noise enhancement of 6.5× over NP magnetite.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".