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Record W2075491369 · doi:10.1149/2.001206esl

Hot Carrier Effect on Gate-Induced Drain Leakage Current in n-MOSFETs with HfO2∕Ti1-xNx Gate Stacks

2012· article· en· W2075491369 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

VenueElectrochemical and Solid-State Letters · 2012
Typearticle
Languageen
FieldEngineering
TopicSemiconductor materials and devices
Canadian institutionsUniversity of British Columbia
FundersNational Science Council
KeywordsMaterials scienceGate dielectricGate oxideOptoelectronicsLeakage (economics)Metal gateOxideNitrideTransistorDielectricThreshold voltageHigh-κ dielectricVoltageElectrical engineeringNanotechnologyLayer (electronics)Metallurgy

Abstract

fetched live from OpenAlex

This paper investigates the effect of channel hot carrier stress (CHCS) on gate-induced drain leakage (GIDL) current in n-type metal-oxide-semiconductor field effect transistor (n-MOSFETs) with HfO2/Ti1-xNx gate stacks. It was found that the behavior of GIDL current during CHCS has dependence with the interfacial layer (IL) oxide thickness of high-k/metal gate stacks. As IL thickness becomes thinner, the GIDL current has a gradual decrease during CHCS, which is contrary to the result of thick-oxide IL devices. Based on the variation of GIDL current (ΔIGIDL) in different stress voltage across gate and drain terminals, trap-assisted band to band holes injection model was proposed to explain the different behavior of GIDL current for different IL thickness. Furthermore, we also investigated the impact of different Ti1-xNx composition of metal gate electrode on the ΔIGIDL after CHCS, and observed that the magnitude of ΔIGIDL decreases with the increase of nitride ratio. This is due to the fact that nitride atoms diffusing from the metal gate fill up oxygen vacancies, and reduce the concentration of traps in high-k dielectric.

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 score0.002
Threshold uncertainty score1.000

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 head0.007
GPT teacher head0.229
Teacher spread0.222 · 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

Citations2
Published2012
Admission routes1
Has abstractyes

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