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Record W2075825080 · doi:10.1103/physrevb.81.045406

Resistivity of thin Cu films coated with Ta, Ti, Ru, Al, and Pd barrier layers from first principles

2010· article· en· W2075825080 on OpenAlexaff
Ferdows Zahid, Youqi Ke, Daniel Gall, Hong Guo

Bibliographic record

VenuePhysical Review B · 2010
Typearticle
Languageen
FieldMaterials Science
TopicCopper Interconnects and Reliability
Canadian institutionsMcGill University
Fundersnot available
KeywordsElectrical resistivity and conductivitySpecular reflectionMaterials scienceScatteringSurface roughnessCondensed matter physicsThin filmSurface finishComposite materialNanotechnologyOpticsPhysics

Abstract

fetched live from OpenAlex

We present an atomistic first-principles calculation for the resistivity of rough Cu thin films coated with barrier layers of Ta, Ti, Ru, Al, and Pd. A significant difference in resistivity due to different barrier metals is found. Ti, Ta, and Ru barriers increase the resistivity whereas Al and Pd lower the resistivity, in comparison with that of bare Cu films having the same degree of roughness disorder. It is found that Al/Pd barrier atoms produce density of states (DOS) that match rather well with the DOS of Cu atoms on a Cu film with a perfectly flat surface while the DOS of Ti, Ta, and Ru do not match. Our results suggest that the geometrical roughness on the Cu film that causes diffuse scattering, can be ``smoothed'' out electronically by certain barriers such that the surface scattering becomes more specular.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.277
Teacher spread0.261 · 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 source (direct Gemma or distilled Codex), 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

Citations74
Published2010
Admission routes1
Has abstractyes

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