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Record W4413464960 · doi:10.1109/tcsi.2025.3593405

Design for Slew-Rate in Multi-Stage CMOS OTAs

2025· article· en· W4413464960 on OpenAlexaff
Mahmood A. Mohammed, Feras Al-Dirini, Ahmed S. Emara, Gordon W. Roberts

Bibliographic record

VenueIEEE Transactions on Circuits and Systems I Regular Papers · 2025
Typearticle
Languageen
FieldChemical Engineering
TopicAnalytical Chemistry and Sensors
Canadian institutionsQueen's UniversityMcGill University
Fundersnot available
KeywordsSlew rateCMOSElectronic engineeringStage (stratigraphy)Integrated circuit designComputer scienceCapacitorElectrical engineeringEngineeringVoltage

Abstract

fetched live from OpenAlex

Cascading gain stages in CMOS Operational Transconductance Amplifiers (OTAs) has become a necessity in applications with high gain requirements, where the contribution of each stage to the overall gain is well-known and carefully designed. Many of these applications also impose requirements on speed, including a minimum Slew-Rate (<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SR</i>) to ensure signal fidelity, however the impact of individual gain stages on the overall <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SR</i> in multi-stage OTAs has been difficult to characterize–let alone carefully design. The difficulty arises due to the complexity of the compensation networks involved in these OTAs. This paper presents a systematic design approach for achieving a target <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SR</i> in multi-stage CMOS OTAs, enabled through the utility of a novel analytical model for estimating the lower-bound Slew-Rate in multi-stage OTAs. The model evaluates individual currents and equivalent capacitances at the output node of each stage, providing insights on the dominant node slowing down the overall <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SR</i>. For generality, the model establishes the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SR</i> analysis based on N-stage designs, and considers widely employed compensation networks. Example designs, with post-layout simulations and measurements of a 3- and a 4-stage CMOS OTA, and with post-layout simulations of a 5-stage CMOS OTA, are presented for validating the model’s utility. The results show strong agreement between theoretical, simulated, and measured <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SR</i> values, confirming the model’s reliability in estimating the lower-bound <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SR</i>, and its utility in a systematic design-for-<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SR</i> approach in multi-stage CMOS OTAs.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.984
Threshold uncertainty score0.770

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.051
GPT teacher head0.272
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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