Impedance Bandwidth Improvement of a Planar Antenna Based on Metamaterial-Inspired T-Matching Network
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Bibliographic record
Abstract
In this paper a metamaterial-inspired T-matching network is directly imbedded inside the feedline of a microstrip antenna to realize optimum power transfer between the front-end of an RF wireless transceiver and the antenna. The proposed T-matching network, which is composed of an arrangement of series capacitor, shunt inductor, series capacitor, exhibits left-handed metamaterial characteristics. The matching network is first theoretically modelled to gain insight of its limitations. It was then implemented directly in the 50- Ω feedline to a standard circular patch antenna, which is an unconventional methodology. The antenna's performance was verified through measurements. With the proposed technique there is 2.7 dBi improvement in the antenna's radiation gain and 12% increase in the efficiency at the center frequency, and this is achieved over a significantly wider frequency range by a factor of approximately twenty. Moreover, there is good correlation between the theoretical model, method of moments simulation, and the measurement results.
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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)
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Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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