Construction of CuS Nanoflakes Vertically Aligned on Magnetically Decorated Graphene and Their Enhanced Microwave Absorption Properties
Bibliographic record
Abstract
Hybrid nanocomposites with enhanced microwave absorption properties have been designed by growing CuS nanoflakes on magnetically decorated graphene, and the effect of special nanostructures on microwave absorption properties has been investigated. The structure of the nanocomposites was characterized by Fourier transform infrared spectra (FTIR), X-ray diffraction (XRD), Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), field emission scanning electron microscope (FESEM), transmission electron microscope (TEM), N2 adsorption-desorption, and vibrating sample magnetometer (VSM). The influence of cetyltrimethylammonium bromide (CTAB) on the morphology of CuS nanoflakes was also investigated. A possible formation process of the nanocomposites and the mechanism of microwave absorption were explained in detail. As an absorber, the nanocomposites with a filler loading of 20 wt % exhibited enhanced microwave absorption properties due to the special nanostructures, extra void space, and synergistic effect. The maximum reflection loss can reach -54.5 dB at 11.4 GHz, and the absorption bandwidths exceeding -10 dB are 4.5 GHz with a thickness of 2.5 mm, which can be adjusted by the thickness. The results indicate that the hybrid nanocomposites with enhanced microwave absorption properties and lightweight have a promising future in decreasing electromagnetic wave irradiation.
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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) | 0.000 | 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".