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Record W2063301368 · doi:10.1149/1.2359100

Deposition Method-Induced Stress Effect on Ultrathin Titanium Nitride Etch Characteristics

2006· article· en· W2063301368 on OpenAlexaff
Mukhtar Hussain, Manuel Quevedo-López, Husam N. Alshareef, Dana Larison, Khusi Mathur, Bruce E. Gnade

Bibliographic record

VenueElectrochemical and Solid-State Letters · 2006
Typearticle
Languageen
FieldEngineering
TopicMetal and Thin Film Mechanics
Canadian institutionsAdvanced Micro Devices (Canada)
Fundersnot available
KeywordsMaterials scienceReflectometryX-ray photoelectron spectroscopyChemical vapor depositionDeposition (geology)Atomic layer depositionEllipsometryNitrideTitanium nitridePhysical vapor depositionLayer (electronics)TitaniumAnalytical Chemistry (journal)Chemical engineeringNanotechnologyThin filmMetallurgyChemistry

Abstract

fetched live from OpenAlex

A systematic study to investigate the fundamental cause for wet etch variation of ultrathin titanium nitride film as a function of the deposition technique such as physical vapor deposition, chemical vapor deposition, and atomic layer deposition is presented. For this study, films were investigated using X-ray diffraction, X-ray photoelectron spectroscopy, X-ray reflectometry, and absolute ellipsometry. It is shown that the deposition method plays an important role on the final crystallography and properties. However, it is demonstrated that the dominating factor defining etch rate is the resulting film strain.

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 score0.025
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 head0.004
GPT teacher head0.206
Teacher spread0.203 · 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

Citations9
Published2006
Admission routes1
Has abstractyes

Explore more

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