Hierarchical porous Ni@boehmite/nickel aluminum oxide flakes with enhanced microwave absorption ability
Bibliographic record
Abstract
In this article, composites consisting of porous Ni cores coated with boehmite/nickel aluminum oxide nanoflakes were successfully prepared by a versatile method. The crystal constituents and shapes of the boehmite/nickel aluminum oxide nanoflakes were strongly influenced by reaction temperature, and their microwave absorption properties were investigated in terms of complex permittivity and permeability. The results reveal that the composites comprising porous Ni cores coated with boehmite/nickel aluminum oxide synthesized at 180 °C present superior absorption properties. The optimal reflection loss is -44.3 dB (>99.99% attenuation) at 14.4 GHz, and the effective absorption (below -10 dB) bandwidth can be monitored in the frequency range of 5.8-18.0 GHz for an absorber with thickness in the range of 1.5-3.5 mm. The high dissipation capability, good impedance match and multiple reflection of the porous flaky structure are responsible for the improvement in microwave absorption. Moreover, a new absorption mechanism was proposed for the porous structure. In this mechanism, the porous structure serves as a spreading container, which attenuates electromagnetic energy by prolonging the travel path and constrains waves in the void space to gradually consume energy. This method paves a new avenue to design porous magnetic-dielectric absorbing materials.
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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".