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Record W4412078816 · doi:10.1080/02564602.2025.2522079

0.35 µm CNTFET for Multi-band Low Noise Amplifier

2025· article· en· W4412078816 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIETE Technical Review · 2025
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Semiconductor Devices and Circuit Design
Canadian institutionsInfineon Technologies (Canada)
Fundersnot available
KeywordsComputer scienceLow-noise amplifierNoise (video)AmplifierTelecommunicationsElectrical engineeringCarbon nanotube field-effect transistorOptoelectronicsMaterials scienceBandwidth (computing)TransistorEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

The potential features of carbon nanotube field-effect transistors (CNTFETs) for designing RF circuit, e.g. a low-noise amplifier (LNA) circuit is demonstrated. However, existing studies have typically focused on LNAs operating in a single band, without extensive investigation into small- and large-signal performances. These circuits should ideally be operated in multi-band to reduce circuit complexity and power consumption with stable operation in the frequency of interest. Therefore, to address these gaps, this paper proposes a dual-band CNTFET LNA designed for 900/1800MHz GSM with a detailed analytical analysis of S-parameters, noise figure, and non-linearity quantified in terms of third-order intercept for the first time. Using these characteristics, a new figure-of-merit is established for comparison with state-of-the-art CMOS technology. Thus this paper addresses the existing research gap in the literature for dual-band CNTFET LNA circuit design.

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.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.763
Threshold uncertainty score0.736

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 head0.041
GPT teacher head0.339
Teacher spread0.298 · 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