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Record W2034474201 · doi:10.1063/1.3608241

Hot carrier effect on gate-induced drain leakage current in high-k/metal gate n-channel metal-oxide-semiconductor field-effect transistors

2011· article· en· W2034474201 on OpenAlexaff
Chih-Hao Dai, Ting‐Chang Chang, Ann‐Kuo Chu, Yuan-Jui Kuo, Szu-Han Ho, Tien-Yu Hsieh, Wen-Hung Lo, Ching-En Chen, Jou-Miao Shih, Wan-Lin Chung, Bai-Shan Dai, Hua-Mao Chen, Guangrui Xia, Osbert Cheng, Cheng Tung Huang

Bibliographic record

VenueApplied Physics Letters · 2011
Typearticle
Languageen
FieldEngineering
TopicSemiconductor materials and devices
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMaterials scienceGate oxideField-effect transistorLeakage (economics)OxideOptoelectronicsTransistorMetal gateMetalElectrical engineeringVoltageMetallurgy

Abstract

fetched live from OpenAlex

This paper investigates the channel hot carrier stress (CHCS) effects on gate-induced drain leakage (GIDL) current in high-k/metal-gate n-type metal-oxide-semiconductor field effect transistors. It was found that the behavior of GIDL current during CHCS is dependent upon the interfacial layer (IL) oxide thickness of high-k/metal-gate stacks. For a thinner IL, the GIDL current gradually decreases during CHCS, a result contrary to that found in a device with thicker IL. Based on the variation of GIDL current at different stress conditions, the trap-assisted band-to-band hole injection model is proposed to explain the different behavior of GIDL current for different IL thicknesses.

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 categoriesMeta-epidemiology (narrow)
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 score0.003
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.018
GPT teacher head0.216
Teacher spread0.197 · 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.

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

Citations36
Published2011
Admission routes1
Has abstractyes

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