A practical approach to model long MIS interconnects in VLSI circuits
Bibliographic record
Abstract
In this paper, a practical approach to model metal-insulator-semiconductor (MIS) interconnects is presented, with focus on the microstrip configuration. Starting from a one-dimensional (1-D) electromagnetic field analysis, we first extend the validity range of some closed-form expressions from 1-D to two-dimensional (2-D) and present an original RLCG-B model with five equivalent circuit parameters. These parameters, which depend on two effective widths of the physical metal strip, can be frequency dependent because of the skin effect and the dielectric losses. The original RLCG-B model is then modified and implemented with seven frequency-independent circuit parameters. These parameters are computed by analytical equations. Numerical simulations are used to validate the original and modified RLCG-B models. A formula to allow comparison of various interconnect models in the time domain is proposed. Comparisons based on this formula are presented for a single transmission line with source resistance, R/sub S/, and load capacitance, C/sub L/. Such comparisons are more meaningful in VLSI applications than comparisons of characteristics derived from swept-frequency per-unit-length parameters.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".