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Record W2060661785 · doi:10.1109/mwsym.2010.5516935

Nonlinear HEMT model direct formulated from the second-order derivative of the I-V/ Q-V characteristics

2010· article· en· W2060661785 on OpenAlex
Linsheng Liu, Jianguo Ma, Haifeng Wu, Geok Ing Ng, Qi‐Jun Zhang

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

Venue2010 IEEE MTT-S International Microwave Symposium · 2010
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsCarleton University
FundersNational Science Foundation
KeywordsHigh-electron-mobility transistorLarge-signal modelNonlinear systemTransistorDerivative (finance)SIGNAL (programming language)Gallium arsenideOrder (exchange)VoltagePhysicsLogic gateMaterials scienceElectrical engineeringTopology (electrical circuits)OptoelectronicsEngineeringComputer scienceQuantum mechanics

Abstract

fetched live from OpenAlex

In this paper, an empirical nonlinear model for high electron mobility transistors (HEMTs) is presented. Unlike the conventional large-signal models whose fitting parameters are coupled to the measured I-V and C-V characteristics, the proposed modeling equations are direct formulated from the second-order derivative of drain current (I-V) and gate charge (Q-V) with respect to gate voltage. As a consequence, the proposed large-signal model is kept continuously differentiable and accurate enough to the higher-order I-V and Q-V derivatives. Measured and modeled results are compared for the 0.25µm gate-length GaAs pseudomorphic HEMTs (pHEMTs), and good agreement is obtained.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.169
Threshold uncertainty score0.916

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 science0.0010.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.207
Teacher spread0.198 · 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