$\text{Ti}_{3} \mathrm{C}_{2} ~\mathrm{T}_{x}$ Mxene Coated Polylactic Acid Horn Antenna for Ku Frequency Band Communications
Bibliographic record
Abstract
Increasing demand for high-performance wireless communications in emerging high-speed and low-latency systems drives innovative methods in antenna designs, fabrications, and manufacturing processes. This work, for the first time, presents polylactic acid (PLA)-based 3D-printed horn antenna coated with$\text{Ti}_{3} \mathrm{C}_{2} ~\mathrm{T}_{x}$MXene from aqueous colloidal solution to produce metallically conductive layer. The fabricated antenna operates at Ku band frequencies (12 to 18 GHz) with simulated gain of$\sim 16.9 \mathbf{d B i}$and measured reflection coefficient of below -16.4 dB. The structure of this horn antenna follows a commercially available metallic antenna with similar dimensions and flange sizes compatible with WR-62 waveguide. In a Tx/Rx configuration where the antennas were located one meter apart from each other, the average magnitude of the transmission coefficient of the MXene-coated antenna demonstrated$\sim 0.25 ~\text{dB}$difference compared to the response of its metallic (aluminum) counterpart over a 6 GHz frequency. Furthermore, this unique method of fabrication resulted in a factor of 3 weight reduction compared to the metallic counterpart, which is important for low-weight and portable antenna arrays. Additionally, a significant manufacturing cost reduction is expected when replacing metal antennas with coated polymer 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) | 0.010 | 0.007 |
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".