Modeling RF Signal Propagation Along On-Chip Interconnects and the Effect of Substrate Doping with the Alternating-Direction-Implicit Finite-Difference Time-Domain (ADI-FDTD) Method
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Bibliographic record
Abstract
The alternating-direction-implicit finite-difference time-domain (ADI-FDTD) method is used to analyze metal-insulator-semiconductor-metal interconnects by solving Maxwell's equations in the time domain. This analysis shows that the silicon substrate losses and the metal line losses can be modeled with high resolution. Our modeling method is supported by experimental data. We find that semiconductors readily operate in the slow wave mode and skin-effect mode for selected doping densities. The ADI-FDTD method is also applied to study the effect of epitaxial layers in different propagating modes. Simulation indicates that inserting epitaxial layers in highly doped substrates should help to keep the signal integrities and reduce substrate noise
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it