Multifunctional Transparent Electromagnetic Surface Based on Solar Cell for Backscattering Reduction
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Advanced electromagnetic (EM) surfaces, namely, metasurfaces, are designed for multifunctional purposes. A glass material with a chessboard configuration is exploited to realize nonabsorbing coating for backscattering reduction. Simultaneously, a solar cell is implemented above the metallic target for light energy harvesting using the transparency feature of the coat. Therefore, two separated aims are obtained in one structure using the plexiglass material and mono solar cell. Initially, the EM wave interactions with both materials are determined. Then, by the use of the wave interactions and scattering theory, two different surfaces are analytically investigated with the aim of transparent backscattering reduction cover. Next, an optimization algorithm is employed to achieve the minimum reflection from the adjacent surfaces. To validate the design performance, a prototype is manufactured. The proposed chessboard cover with plexiglass material is numerically and experimentally analyzed and compared together, having an acceptable agreement. The experimental results indicate a 75% bandwidth for backscattering reduction. In addition, the proposed structure can give promising opportunities to enhance the scattering properties with simultaneous power harvesting, which could generate critical advantages for real-world applications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it