Enhancement of printed inductors using artificial magnetic conductor (AMC) surfaces for millimeter-wave applications
Bibliographic record
Abstract
Integrated inductors are one of the most basic elements used in the design of modern electronic systems. However, they generally suffer from poor quality and are inherently area intensive, thus limiting system performance and prove to be a bottleneck for compact system integration. Several research efforts have been devoted to the development of miniaturized, high quality inductors. One such method proposes the use of an Artificial Magnetic Conductor (AMC) surface to enhance the inductor performance by creating a second inductive region thereby enabling inductor reuse. It can theoretically be shown, through image theory, that an AMC reflector can be used to effectively double the inductance of an inductor component. Accordingly, in order to validate this concept, two AMC surface designs are investigated for both on-chip and PCB-based implementations. The designed AMC surfaces are then integrated with standard loop inductor components in order to justify their performance benefits through measurement results of the fabricated prototypes. Finally, the practicality of this approach is demonstrated through the application of mm-wave VCOs by replacing a standard LC-VCO tank inductor with a miniaturized AMC-backed inductor. In order to do so, mm-wave LC-VCO prototypes are designed, fabricated and characterized through measurements.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".