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Record W2196069668 · doi:10.1109/tim.2015.2477240

Contactless Test Access Mechanism for TSV-Based 3-D ICs Utilizing Capacitive Coupling

2015· article· en· W2196069668 on OpenAlexafffund
Iftekhar Basith, Rashid Rashidzadeh

Bibliographic record

VenueIEEE Transactions on Instrumentation and Measurement · 2015
Typearticle
Languageen
FieldEngineering
Topic3D IC and TSV technologies
Canadian institutionsUniversity of Windsor
FundersCMC Microsystems
KeywordsThrough-silicon viaCapacitive couplingCapacitive sensingMaterials scienceElectronic engineeringThree-dimensional integrated circuitCMOSIntegrated circuitInsertion lossCoupling (piping)WaferOptoelectronicsSignal integrityElectrical engineeringEngineeringPrinted circuit boardVoltage

Abstract

fetched live from OpenAlex

Through silicon via (TSV) is considered an enabling technology for 3-D integrated circuit (IC) integration. Testing 3-D ICs with multiple stacked dies is a challenging task. Probing a TSV for the purpose of testing with conventional wafer probes can undermine its physical integrity. In this paper, a contactless TSV probing method using capacitive coupling is presented. The proposed solution eliminates the risks of direct TSV probing and supports the high-density and fine-pitch requirements for TSV probing. 3-D full-wave simulations indicate that a strong electric field is formed between the probe and the TSV when the distance between them falls below 5 μm. The measurement results on a prototype fabricated with CMOS 65-nm technology show that the proposed TSV probing scheme presents a -55-dB insertion loss at 1-GHz frequency. The probe can be used up to a data rate of 5 Gbits/s while maintaining higher than 35-dB signal-to-noise ratio.

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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.120
GPT teacher head0.284
Teacher spread0.165 · 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

Citations13
Published2015
Admission routes2
Has abstractyes

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