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Record W2107360972 · doi:10.1109/tdmr.2003.815285

Nondestructive void size determination in copper metallization under passivation

2003· article· en· W2107360972 on OpenAlexfundno aff
Zhenghao Gan, Cher Ming Tan, Guan Zhang

Bibliographic record

VenueIEEE Transactions on Device and Materials Reliability · 2003
Typearticle
Languageen
FieldEngineering
TopicIntegrated Circuits and Semiconductor Failure Analysis
Canadian institutionsnot available
FundersMinistry of Education, IndiaUniversité de Sherbrooke
KeywordsPassivationMaterials scienceVoid (composites)ElectromigrationNondestructive testingCopperCathode rayWedge (geometry)Finite element methodScanning electron microscopeCurrent (fluid)Composite materialVoltageMetallurgyElectronOpticsStructural engineeringElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

A novel nondestructive failure analysis technique to rapidly locate tiny voids in narrow metallization line covered with passivation is proposed, based on the simulation results. In this technique, the current alteration in a metal line under study is recorded continuously when it is subjected to electron beam scanning and biased by a small external voltage. Finite-element analysis is performed to simulate the temperature distribution and current alteration in the metal line. The electron-beam heating is demonstrated as the most important factor contributing to the current alteration. Reconstruction of voids with any shape (such as wedge or slit) is possible on the basis of the gradient of the current alteration. It is found that the minimum detectable void size can be as low as 50 nm. Experimental verification of the technique is underway.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.010
GPT teacher head0.219
Teacher spread0.210 · 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

Citations4
Published2003
Admission routes1
Has abstractyes

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