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Record W2319599348 · doi:10.1109/tcpmt.2014.2377375

Capacitance and Conductance of Through Silicon Vias With Consideration of Multilayer Media and Different Shapes

2015· article· en· W2319599348 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

VenueIEEE Transactions on Components Packaging and Manufacturing Technology · 2015
Typearticle
Languageen
FieldEngineering
Topic3D IC and TSV technologies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsCapacitanceConductanceMaterials scienceRADIUSSiliconOptoelectronicsAcousticsOpticsPhysicsCondensed matter physicsComputer scienceElectrode

Abstract

fetched live from OpenAlex

This paper evaluates the capacitance and conductance of the through silicon vias (TSVs) with consideration of the multilayer media along the vertical direction and different shapes. According to the moment method, the capacitance and conductance of the straight and two types of tapered TSVs are calculated and compared with those of the conventional 2-D method. It is shown that the capacitance calculated by the 2-D method for the straight TSVs will produce a large error when the radius and pitch of the TSVs become larger. For the two types of tapered TSVs, their capacitance decreases with the increase in the slop angle and the pitch due to less surface area and capacitance coupling, respectively. Therefore, the tapered TSVs with larger slop angle and pitch are beneficial to reduce the propagation delay. With the increase in the pitch, the conductance of both the straight and the tapered TSVs increases slightly at low frequency, while it decreases at high frequency. All the results by the method in this paper agree well with those of the electromagnetic simulations up to 40 GHz.

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)0.000
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 score0.142
Threshold uncertainty score0.596

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.031
GPT teacher head0.220
Teacher spread0.189 · 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