MétaCan
Menu
Back to cohort

A Family of Physics-Based Models for Monolithic GaN Integration

2024· article· en· W4404295352 on OpenAlexaff
Lan Wei, Ryan Fang, Yijing Feng, Johan Alant, Dongyan Xu, Tanya Rampal, Ujwal Radhakrishna

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGaN-based semiconductor devices and materials
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPhysicsEngineering physicsComputer scienceMaterials scienceOptoelectronics

Abstract

fetched live from OpenAlex

This paper provides a brief overview of the family of physics-based MIT Virtual-source Gallium-nitride (MVSG) compact models, including those for Gallium-nitride (GaN) based transistors, multi-channel Schottky diodes, and transmission line (TLM) structures with nonlinear resistance. A coherent model formulation has been adopted across these devices through a modular approach using a universal set of basic modules. We will introduce the the model formulation and the basic modules with the explanation of underlining device phyiscs. Various features, including those non-linear effects critical for GaN applications, such as trapping, self heating, will also be explained and demonstrated. Given its accuracy, scalability and flexibility, this coherent family of physics-based GaN device compact models provide a solid foundation for the development of Process Design Kit for monolithic GaN technology.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.569
Threshold uncertainty score0.330

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 head0.036
GPT teacher head0.280
Teacher spread0.243 · 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 designBench or experimental
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

Citations1
Published2024
Admission routes1
Has abstractyes

Explore more

Same topicGaN-based semiconductor devices and materialsFrench-language works237,207