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Recent progress in micro and nano-joining

2009· article· en· W2032198583 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Physics Conference Series · 2009
Typearticle
Languageen
FieldEngineering
TopicLaser Material Processing Techniques
Canadian institutionsUniversity of Waterloo
FundersCanada Research Chairs
KeywordsMaterials scienceMicroelectronicsWeldingCarbon nanotubeNano-BrazingNanotechnologyLaserFemtosecondCold weldingMetallurgyLaser beam weldingComposite materialOpticsGas metal arc weldingAlloy

Abstract

fetched live from OpenAlex

Micro and nano-joining has been identified as a key enabling technology in the construction of micromechanical and microelectronic devices. The current article reviews recent progress in micro and nano-joining. In particular, laser micro-welding (LMW) of crossed 316 LVM stainless steel (SS) wire was compared to conventional resistance micro-welding (RMW) and was successfully employed in welding a Pt-Ir /SS dissimilar combination. Welding of Au nanoparticles was realized using femtosecond laser irradiation and its application in the surface enhanced Raman spectroscopy was investigated. Brazing between carbon nanotube (CNT) bundles and Ni electrodes was attained in vacuum, resulting in the development of a novel CNT filament of incandescent lamps.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.754
Threshold uncertainty score0.337

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 communication0.0000.001
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 head0.016
GPT teacher head0.242
Teacher spread0.226 · 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