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Record W2667104373 · doi:10.1109/tdmr.2017.2716943

Wet Metallization of High Aspect Ratio TSV Using Electrografted Polymer Insulator to Suppress Residual Stress in Silicon

2017· article· en· W2667104373 on OpenAlexafffund
T Dequivre, Gitanjali Kolhatkar, Azza Hadj Youssef, Xuan Tuan Le, Gessie Brisard, Andreas Ruëdiger, Serge A. Charlebois

Bibliographic record

VenueIEEE Transactions on Device and Materials Reliability · 2017
Typearticle
Languageen
FieldEngineering
Topic3D IC and TSV technologies
Canadian institutionsDalsa CorporationInstitut National de la Recherche ScientifiqueInstitut interdisciplinaire d'innovation technologiqueUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMicrosystemMaterials scienceResidual stressSiliconThrough-silicon viaSilicon on insulatorReliability (semiconductor)Stress (linguistics)FabricationPolymerOptoelectronicsComposite materialElectronic engineeringNanotechnologyEngineering

Abstract

fetched live from OpenAlex

Through-silicon-vias (TSV) are the key to 3-D integrated microsystems. Their fabrication leads to reliability issues linked to the thermo-mechanical stress induced in the silicon around the vias. In this paper, we propose reducing the silicon residual stress in high aspect ratio copper TSVs (HAR TSV) using an electrografted polymer insulator, poly-4-vinylpyridine (P4VP), to replace the traditional silicon oxide layer. We use Raman spectroscopy to make the first investigation of the residual stress in the Si around P4VP-insulated TSVs and compare it to SiO2-insulated TSVs. The results show that P4VP acts as a stress buffer layer because of its particular mechanical properties as the measured residual stress in Si is significantly reduced at room temperature around the polymer insulated HAR TSVs. The potential benefits of such a technology are not only better thermo-mechanical reliability of a 3-D integrated microsystem but also greater integration density.

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)0.000
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
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.015
GPT teacher head0.250
Teacher spread0.235 · 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

Citations9
Published2017
Admission routes2
Has abstractyes

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Same venueIEEE Transactions on Device and Materials ReliabilitySame topic3D IC and TSV technologiesFrench-language works237,207