Study on Single Event Transients in Amplifier for Switched-Capacitor Circuits in CMOS Technology
Bibliographic record
Abstract
This article presents a comprehensive analysis of the sensitivity of different switched-capacitor amplifier circuits to Single Event Transients (SETs). SETs are temporary variations in circuit output voltage or current caused by the interaction of heavy ions or high-energy protons with sensitive device nodes. The study focuses on three types of amplifier circuits commonly used in Multiplying Digital-to-Analog Converter (MDAC) stages of state-of-the-art pipelined ADCs: operational amplifier (Op-Amp) MDACs, comparator-based switched-capacitor (CBSC) MDACs, and ring amplifier (RAMP) based MDACs. By employing a TCAD-calibrated double exponential transient current pulse model, we simulate the SET responses resulting from heavy ion strike experiments on sensitive nodes of each MDAC type. Our analysis and simulations reveal the amplitude and recovery time of the output results for each MDAC type when subjected to SETs. Notably, we propose a novel radiation hardening solution: the parallel-auxiliary ring amplifier (PA-RAMP) structure, which demonstrates significantly better tolerance to SETs compared to other designs. This research not only contributes to the understanding of SET effects on analog switched-capacitor amplifier circuits but also introduces a cost-effective approach to mitigate these effects. As technology nodes scale down and circuits become more susceptible to SETs, the PA-RAMP structure offers a promising solution for radiation-hardened applications, enabling the use of scaling-friendly RAMPs with enhanced tolerance to SETs.
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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) | 0.000 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".