Development and Characterization of Stable Polymer Formulations for Manufacturing Magnetic Composites
Why this work is in the frame
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Bibliographic record
Abstract
Polymer bonded permanent magnets find significant applications in a multitude of electrical and electronic devices. In this study, magnetic particle-loaded epoxy resin formulations were developed for in-situ polymerization and material jetting based additive manufacturing processes. Fundamental material and process issues like particle settling at room temperature and elevated temperature curing, rheology control and geometric stability of the magnetic polymer during the thermal curing process are addressed. Control of particle settling, modifications in rheological behavior and geometric stability were accomplished using an additive that enabled the modification of the formulation behavior at different process conditions. The magnetic particle size and additive loading were found to influence the rheological properties significantly. The synergistic effect of the additive enabled the developing of composites with engineered magnetic filler loading. Morphological characterization using scanning electron microscopy revealed a homogenous particle distribution in composites. It was observed that the influence of temperature was profound on the coercive field and remanent magnetization of the magnetic composites. The characterization of magnetic polymers and composites using rheometry, scanning electron microscopy, X-ray diffraction and superconducting quantum interference device (SQUID) magnetometry analysis enabled the correlating of the behavior observed in different stages of the manufacturing processes. Furthermore, this fundamental research facilitates a pathway to construct robust materials and processes to develop magnetic composites with engineered properties.
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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 | 0.000 |
| 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 it