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Record W4416885424 · doi:10.37665/srlerwz21052

Solder-Directed Self-Assembly by Different-Melting-Points and Capillary Forces for Highly-Integrated Microelectronics/Mems Systems

2008· article· W4416885424 on OpenAlexaff
Mei Liu, Jun Yang

Bibliographic record

VenueSoldering and Reliability Conferences · 2008
Typearticle
Language
FieldEngineering
TopicModular Robots and Swarm Intelligence
Canadian institutionsWestern University
Fundersnot available
KeywordsCapillary actionMicrofabricationSiliconProcess (computing)Substrate (aquarium)Soldering

Abstract

fetched live from OpenAlex

ABSTRACT Self-assembly has been widely accepted as the next generation technology of integrating highly dense MEMS/microelectronics systems, in particular for complex and hybrid systems composed of various components. In this paper we demonstrate the use of hybrid self-assembly for integration of different kinds of freestanding micrometer-scale micro-parts onto one common substrate, which is achieved through patterning solders with different melting points to designated binding sites on the substrate, and activating them separately and sequentially. Capillary force of molten solder is used to realize final bonding. We outline the microfabrication process of the substrate and silicon micro-parts and demonstrate this hybrid selfassembly technique.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.838
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.013
GPT teacher head0.213
Teacher spread0.200 · 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.

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

Citations0
Published2008
Admission routes1
Has abstractyes

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