EMI Shielding Using Flexible Optically Transparent Screens for Smart Electromagnetic Environments
Bibliographic record
Abstract
Past generations of wireless systems focused largely toward power and bandwidth to support higher data rates, coverage, and quality of service. Smart electromagnetic environments, on the other hand, are aimed at meeting these expectations through modifications in the electromagnetic properties of the geometry, which were once considered an uncontrollable part of a wireless system. This is done through careful placement of smart electromagnetic structures that can constructively manipulate the propagation of electromagnetic waves. In this work, we present optically transparent electromagnetic screens for shielding applications that require visual observation. New aluminum-doped zinc oxide (AZO) thin films, that are low-loss, and optically transparent, are deposited on plastic for use as absorbing-type shields. We also present a simple and reliable technique to fabricate all-metallic single-layer reflecting-type shields. All these shields have a unique combination of shielding effectiveness (SE) and optical transparency that advance the state of the art. They can be used as curtains or walls in indoor environments, windows for autonomous vehicles and as covers to shield smart IoT devices.
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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".