On-Chip Terahertz antenna array based on amalgamation of metasurface-inspired and artificial magnetic conductor technologies for next generation of wireless electronic devices
Bibliographic record
Abstract
The paper presents a feasibility study on an innovative terahertz (THz) on-chip antenna array designed to reliably meet the high-performance connectivity requirements for next generation of wireless devices to enable bandwidth intensive applications, superfast fast streaming, bulk data exchange between internet of things (IoT) devices/smartphones and the development of holographic video conferencing. The significantly smaller wavelength of the THz-band and metasurface-inspired and artificial magnetic conductor (AMC) technologies are exploited here to realize an on-chip antenna. Several experimental on-chip antenna arrays of various matrix sizes were investigated for application at millimeter-wave/Terahertz RF front-end transceivers. The technique proposed here is shown to enhance the antennas impedance bandwidth, gain and radiation efficiency. Purely for experimental purposes a 2 × 24 radiation element array was fabricated. It exhibits an average measured gain of 20.36 dBi and radiation efficiency of 37.5% across 0.3–0.314 THz. For proof of the concept purposes a THz receiver incorporating the proposed on-chip antenna was modelled. The results show that with the proposed antenna array a THz receiver can provide a gain of 25 dB when the antenna is directly matched to low-noise amplifier stage.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".