A Shifted-Beam Method for Near-Field Wireless Power Transfer using Parasitic Arrays
Bibliographic record
Abstract
Optimizing near field (NF) wireless power transfer (WPT) to ensure maximum power transfer efficiency (PTE) is essential for a number of applications such as radio-frequency identification (RFID) and device charging. A new WPT method using a parasitic array is proposed, inspired by a shifted-beam (SB) wave interference technique for field focusing. The SB method is implemented for target distances between$\mathbf{1}\lambda$and$\mathbf{2}\lambda$at 2.4 GHz$(\lambda=12.5\ \text{cm})$, which lie roughly in the radiative NF. PTE from the SB method is compared with results from a uniformly excited array of similar length, as well as a phase optimization (PO) method based on conjugate-phase (CP) focusing. The transmit$(\mathrm{T}_{\mathrm{x}})$system is implemented as an array of center-fed dipoles, with a$\mathbf{0.48}\lambda$non-excited dipole used as the receive$(\mathrm{R}_{\mathrm{x}})$element. The results show an enhancement of PTE compared to the baseline uniform array, and in some cases the PO array. The simplicity of the SB method makes it an advantageous design choice.
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".