A Compact High-Speed Capacitive Data Transfer Link With Common Mode Transient Rejection for Isolated Sensor Interfaces
Bibliographic record
Abstract
In this article, a compact differential data transfer link architecture for isolated sensor interfaces (SIs) and immune to common mode transients (CMTs) is presented. The proposed architecture shows low latency supporting high-speed transmission with a low bit error rate (BER) in the presence of CMT noise for applications, such as data acquisition, biomedical equipment, and communication networks. In transportation applications, motors and actuators are subjected to harsh environmental conditions, e.g., lightning strikes and abnormal voltage operations. These conditions introduce noise and can cause damage to small electronics due to high-voltage power surges. To ensure human safety and circuitry protection, a data transfer system must be implemented between high-voltage and low-voltage domains. The proposed design has been simulated using Cadence tools, and a prototype has been manufactured in a 0.18-$\mu $m CMOS process. The fabricated prototype consumes an effective silicon area of$37.2\times 10^{3}~\mu $m2and can sustain a breakdown voltage of 710 Vrms. Experimental results show that the proposed solution achieves a CMT immunity (CMTI) of 2.5 kV/$\mu $s at a data rate of 480 Mb/s with a BER of$10^{-12}$. The propagation delay is 3.9ns with a 4 ps/°C variation rate over temperatures ranging from$- 31~^{\circ }$C to$100~^{\circ }$C. Under typical test conditions, the BER reaches$10^{-15}$with a peak-to-peak data dependent jitter (DDJ) of 29.8ps.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".