Efficient Electromagnetic Wave Absorption and Thermal Infrared Stealth in PVTMS@MWCNT Nano-Aerogel via Abundant Nano-Sized Cavities and Attenuation Interfaces
Bibliographic record
Abstract
Abstract Pre-polymerized vinyl trimethoxy silane (PVTMS)@MWCNT nano-aerogel system was constructed via radical polymerization, sol–gel transition and supercritical CO2 drying. The fabricated organic–inorganic hybrid PVTMS@MWCNT aerogel structure shows nano-pore size (30–40 nm), high specific surface area (559 m2 g−1), high void fraction (91.7%) and enhanced mechanical property: (1) the nano-pore size is beneficial for efficiently blocking thermal conduction and thermal convection via Knudsen effect (beneficial for infrared (IR) stealth); (2) the heterogeneous interface was beneficial for IR reflection (beneficial for IR stealth) and MWCNT polarization loss (beneficial for electromagnetic wave (EMW) attenuation); (3) the high void fraction was beneficial for enhancing thermal insulation (beneficial for IR stealth) and EMW impedance match (beneficial for EMW attenuation). Guided by the above theoretical design strategy, PVTMS@MWCNT nano-aerogel shows superior EMW absorption property (cover all Ku-band) and thermal IR stealth property (ΔT reached 60.7 °C). Followed by a facial combination of the above nano-aerogel with graphene film of high electrical conductivity, an extremely high electromagnetic interference shielding material (66.5 dB, 2.06 mm thickness) with superior absorption performance of an average absorption-to-reflection (A/R) coefficient ratio of 25.4 and a low reflection bandwidth of 4.1 GHz (A/R ratio more than 10) was experimentally obtained in this work.
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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".