Reconfigurable screen-printed terahertz frequency selective surface based on metallic checkerboard pattern
Bibliographic record
Abstract
Abstract We employed the screen-printing method to fabricate terahertz (THz) frequency selective surfaces (FSSs) featuring an inductive metallic checkerboard (i-MCB) pattern based on conductive silver ink onto a flexible polyethylene terephthalate substrate, chosen for its excellent THz transmission properties below 1 THz [Jin et al 2006 J. Korean Phys. Soc. 49 513–17]. Analytical studies, along with simulations and experiments, were conducted to investigate the filtering characteristics of the printed FSSs, confirming their functionality as a band-pass filter. Subsequently, we demonstrated the reconfigurability of a two-layer system by vertically stacking two layers. This was achieved by systematically shifting the position of the second layer in the x or y-direction relative to the first layer. Experimental verification revealed a significant variation in normalized transmission, ranging from 94% to 6% at 0.15 THz for type-I:i-MCBs and 90% to 5% at 0.20 THz for type-II:i-MCBs, respectively. This study presents a simple scheme for a reconfigurable screen-printed i-MCB-FSS operating in the THz range. Consequently, our findings demonstrate that screen printing method can effectively be employed for the large-scale production of THz FSSs.
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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".