MétaCan
Menu
Back to cohort
Record W3047812573 · doi:10.1109/ectc32862.2020.00352

Design and fabrication of an ultra-thin silicon vapor chamber for compact electronic cooling

2020· preprint· en· W3047812573 on OpenAlexaff
Quentin Struss, P. Coudrain, Jean-Philippe Colonna, A. Souifi, Christian Gontrand, Edouard Deschaseaux, Gaëlle Mauguen, V. Mathieu, T. Magis, Gilles Simon, Luc G. Fréchette

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicHeat Transfer and Boiling Studies
Canadian institutionsInstitut interdisciplinaire d'innovation technologiqueUniversité de Sherbrooke
FundersAgence Nationale de la Recherche
KeywordsMicroelectronicsFabricationWaferMaterials scienceSiliconIntegrated circuitOptoelectronics

Abstract

fetched live from OpenAlex

This paper presents the design and the fabrication of an ultra-thin vapor chamber exclusively composed of silicon, aimed to be integrated in microelectronic chips to spread high-density hot spots. A process flow fully compatible with the presence of a circuit on the front side has been developed and a 1 x 1 cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> prototype with an internal vapor cavity and a wick thickness of 210 μm has been designed and fabricated. The wick is composed of a matrix of micropillars with 5 μm diameter and 30 μm high in a square arrangement. The cavity is obtained by plasma activated direct bonding of two wafers with complementary cavities. The spreading performances have been estimated by a finite element method (FEM) modeling and presents higher performances compared to copper heat spreader with 4°C less temperature difference for a 4 W and 1 × 1 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> hotspot.

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 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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.777
Threshold uncertainty score0.805

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 head0.037
GPT teacher head0.271
Teacher spread0.234 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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
Published2020
Admission routes1
Has abstractyes

Explore more

Same topicHeat Transfer and Boiling StudiesFrench-language works237,207