Liquid-templated graphene aerogel electromagnetic traps
Bibliographic record
Abstract
) elastic anti-reflection aerogels, altering their shielding mechanism from dominant reflection (reflectance >0.8) to absorption (absorbance >0.7) by trapping EM waves inside the aerogel. The aerogel EM traps were generated using interfacial complexation, yielding engineerable filamentous liquid structures. These served as templates for aerogel creation through a follow-up process of freezing and lyophilization. The engineerable lossy medium of aerogels benefits from a multi-scale porous construct with the combined action of dielectric and conduction losses, highly dissipating the EM waves and minimizing the reflections. Notably, declining the diameter of aerogel filaments promoted its absorption dominancy, rendering it a potent dissipating medium for EM waves. Pairing a metallic substrate with filamentous aerogel EM traps has resulted in an exceptionally effective absorption-dominant shielding system, achieving absorbance levels between 0.70-0.81. This system offers a shielding effectiveness of 53-89 dB within the X-band frequency range. This innovation addresses a persistent issue in shielding science related to the reflective characteristics of metallic substrates, effectively inhibiting their induced EM reflections.
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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) | 0.001 | 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".