Ultrahigh Electromagnetic Wave Transmitting Polyphenylene Sulfide Microcellular Foams Based on Molecular Structure Design for 5G Communication
Bibliographic record
Abstract
In the scenario of fifth-generation communication, especially millimeter wave (mmW) transmission, microelectronic material is required to have better signal stability, that is, a lower dielectric constant ( D k ) and dielectric loss ( D f ). This work takes full advantage of the low dielectric molecular structure characteristics in polyphenylene sulfide (PPS) and the nonresidual low dielectric characteristics of supercritical CO 2 (scCO 2 ) foaming to enhance the low dielectric performance. The distinct structure of a highly stable thioether bond and highly reactive hydrogen in the benzene ring in the PPS macromolecule enables the oxo-bridging between PPS molecular chains and hence increases PPS melt strength. By further adjusting the regularity in PPS molecular chains to broaden the melting range of PPS crystals, the PPS microcellular foam of large expansion ratio (16.5-fold) with uniform cells is obtained. It has an ultralow D k of 1.14 and D f of 0.0005 at 3 GHz. In the Ka band of 26–40 GHz, the broadband signal transmission has nearly no loss (∼99%). Furthermore, it has a low density (<0.08 g/cm 3 ), is hydrophobic (contact angle of 123.4°), and reaches V-0 level flame retardancy. This ultrahigh mmW transmission material with excellent comprehensive performance provides an alternative for solving the problems of mmW propagation in the existing dielectric 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) | 0.001 | 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".