A magnetic poly(dimethylesiloxane) composite membrane incorporated with uniformly dispersed, coated iron oxide nanoparticles
Bibliographic record
Abstract
We report a new magnetic polymer membrane for MEMS application. The polymeric magnetic composite has coated iron oxide nanoparticles incorporated in a polydimethylsiloxane (PDMS) matrix. Existing magnetic polymeric materials have particle agglomeration problems, which result in rough surfaces and uneven mechanical and optical properties. We show that the use of iron oxide nanoparticles (10 nm in diameter) with fatty acid and hydrophobic coatings inhibits aggregation of particles in the PDMS polymer matrix. Agglomerated particle sizes in thin-film PDMS composites incorporated with uncoated and coated particles are 51 ± 24 µm and 1.6 ± 0.25 µm, respectively. The PDMS composites exhibit saturation magnetization of 22.8 to 23.94 emu g−1. Stress–strain curves of the composites are characterized by tensile tests. Free-standing magnetic PDMS membranes are fabricated in different sizes from 4 mm to 7 mm in diameter and with the thickness of 35.5 ± 1.5 µm. The membrane of 7 mm diameter achieves deflection of 625 µm in a 0.417 T magnetic field. The magnetic PDMS membranes may be used in micro-pumps and lab-on-a-chip applications.
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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 | 0.001 | 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".