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Record W2031281329 · doi:10.1115/1.4006137

Interconnect Joule Heating under Transient Currents using the Transmission Line Matrix Method

2012· article· en· W2031281329 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 Electronic Packaging · 2012
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Simulation and Numerical Methods
Canadian institutionsAdvanced Micro Devices (Canada)
Fundersnot available
KeywordsTransient (computer programming)Joule heatingTransmission lineMicroelectronicsTransmission-line matrix methodInterconnectionResistorMechanicsMaterials scienceReliability (semiconductor)Matrix (chemical analysis)ElectromigrationElectric power transmissionElectronic engineeringElectrical engineeringEngineeringPhysicsComputer scienceVoltageOptoelectronicsThermodynamicsComputational electromagneticsComposite material

Abstract

fetched live from OpenAlex

The quality and reliability of interconnects in microelectronics is a major challenge considering the increasing level of integration and high current densities. This work studied the problem of transient Joule heating in interconnects in a two-dimensional (2D) inhomogeneous domain using the transmission line matrix (TLM) method. Computational efficiency of the TLM method and its ability to accept non-uniform 2D and 3D mesh and variable time step makes it a good candidate for multi-scale analysis of Joule heating in on-chip interconnects. The TLM method was implemented with link-resistor (LR) and link-line (LL) formulations, and the results were compared with a finite element (FE) model. The overall behavior of the TLM models were in good agreement with the FE model while, near the heat source, the transient TLM solutions developed slower than the FE solution. The steady-state results of the TLM and FE models were identical. The two TLM formulations yielded slightly different transient results, with the LL result growing slower, particularly at the source boundary and becoming unstable at short time-steps. It was concluded that the LR formulation is more accurate for transient thermal analysis.

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)0.002
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.680
Threshold uncertainty score0.516

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 integrity0.0000.001
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 head0.029
GPT teacher head0.364
Teacher spread0.335 · 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