MétaCan
Menu
Back to cohort

High-CMRR, Operational Transconductance Amplifier for Low-Voltage Applications Based on a Degenerative Current TRAM

2024· article· en· W4400233358 on OpenAlexaff
Majid Radman, Amir M. Sodagar

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Semiconductor Devices and Circuit Design
Canadian institutionsYork University
FundersNational Science Foundation
KeywordsOperational transconductance amplifierTransconductanceOperational amplifierElectrical engineeringAmplifierCurrent (fluid)Electronic engineeringVoltageComputer scienceEngineeringCMOSTransistor

Abstract

fetched live from OpenAlex

This paper introduces an innovative circuit scheme named 'Current TRAM,' leveraging a degenerative current steering mechanism through the implementation of three current mirrors within a closed-loop configuration. This configuration undergoes transformation into a fully differential voltage-to-current converter, demonstrating its application in the design of an integrated operational transconductance amplifier (OTA). The OTA offers a high gain-bandwidth and common-mode rejection ratio at low power. Diode-connected topologies in the current mirrors adaptively bias other transistors, eliminating the need for a common-mode feedback circuit. A common-source amplifier is employed at the output stage of the OTA to enhance the slew rate performance. Implemented in a standard 0.18 µm CMOS process with a supply voltage of 0.4 V, the proposed OTA achieves a gain-bandwidth (GBW) product of 23 kHz, a DC gain of 75 dB, and a slew rate of 15.5 V/ms. Remarkably, it accomplishes this while consuming a mere 37 nW of power and driving a capacitive load of 2 × 15 pF.

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: Methods · Consensus signal: none
Teacher disagreement score0.985
Threshold uncertainty score0.707

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 head0.023
GPT teacher head0.279
Teacher spread0.255 · 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
GenreMethods

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

Citations1
Published2024
Admission routes1
Has abstractyes

Explore more

Same topicAdvancements in Semiconductor Devices and Circuit DesignFrench-language works237,207