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Record W2050756245 · doi:10.1117/12.525802

Wafer-level vacuum packaging technology based on selective electroplating

2004· article· en· W2050756245 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

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2004
Typearticle
Languageen
FieldEngineering
Topic3D IC and TSV technologies
Canadian institutionsInstitut National d'Optique
Fundersnot available
KeywordsElectroplatingWaferVacuum packingWafer-level packagingMaterials scienceManufacturing engineeringDie preparationProcess engineeringOptoelectronicsEngineeringMechanical engineeringNanotechnologyWafer dicing

Abstract

fetched live from OpenAlex

A novel concept for low-cost, wafer-level packaging of MEMS is proposed and applied to vacuum packaging of INO’s 160x120 pixel uncooled bolometric focal plane arrays, FPAs, based on vanadium oxide thermistor material. A wafer-scale metallic tray composed of several tens of micropackages is electroplated by using the thick resist SU-8 as a micromold. FPA dies and infrared windows are then soldered to the main tray by flip-chip bonding. Contrary to the conventional wafer to wafer bonding approach, assembly and vacuum sealing steps are dissociated. For this purpose, each micropackage is equipped with a pump-out hole for outgassing under vacuum and at elevated temperature prior to vacuum sealing. The process flow for fabrication of micropackages is described. The influence of DC and pulse plating conditions on the stress and properties of deposited nickel packages was investigated. Results on the selective electroplating of indium solder on antireflection-coated IR window wafers and the formation of a solderable layer around the chip are presented.

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 categoriesMeta-epidemiology (narrow)
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 score0.442
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.213
Teacher spread0.203 · 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