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Record W3118188372 · doi:10.1116/6.0000617

Novel physics-based tool-prototype for electromigration assessment in commercial-grade power delivery networks

2020· article· en· W3118188372 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Vacuum Science & Technology B Nanotechnology and Microelectronics Materials Processing Measurement and Phenomena · 2020
Typearticle
Languageen
FieldMaterials Science
TopicCopper Interconnects and Reliability
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsElectromigrationVoltage dropInterconnectionMonte Carlo methodPower network designVoltageDrop (telecommunication)GridElectronic circuitElectronic engineeringMaterials scienceComputer scienceElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

A recently developed novel methodology for electromigration (EM) failure assessment in power/ground grids of integrated circuits is employed in the electronic design automation tool prototype. The tool performs the analysis of stress evolution in interconnect trees for detecting EM-induced voiding locations and tracks resistance increase in the voided wires based on a physics-based model of voiding kinetics. Increased resistances of the branches of power/ground networks lead to a voltage drop increase in grid nodes. The instance in time when a designer-specified voltage-drop threshold is reached defines the EM-induced time-to-failure. Monte-Carlo simulation, performed around the core engine that simulates the stress over time using randomly generated atomic diffusivities and critical stress values, leads to the mean-time-to-failure of the grid, along with voiding probabilities of the interconnect branches.

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.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.070
Threshold uncertainty score0.897

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.023
GPT teacher head0.261
Teacher spread0.238 · 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