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Record W2980652891 · doi:10.1088/2631-7990/ab4d51

Femtosecond laser additive and subtractive micro-processing: enabling a high-channel-density silica interposer for multicore fibre to silicon-photonic packaging

2019· article· en· W2980652891 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

VenueInternational Journal of Extreme Manufacturing · 2019
Typearticle
Languageen
FieldEngineering
TopicLaser Material Processing Techniques
Canadian institutionsUniversity of Toronto
FundersHuawei Technologies
KeywordsInterposerMaterials sciencePhotonicsFemtosecondLaserOptoelectronicsSilicon photonicsElectronic engineeringNanotechnologyComputer scienceEtching (microfabrication)OpticsEngineering

Abstract

fetched live from OpenAlex

Abstract Great strides have been made over the past decade to establish femtosecond lasers in advanced manufacturing systems for enabling new forms of non-contact processing of transparent materials. Research advances have shown that a myriad of additive and subtractive techniques is now possible for flexible 2D and 3D structuring of such materials with micro- and nano-scale precision. In this paper, these techniques have been refined and scaled up to demonstrate the potential for 3D writing of high-density optical packaging components, specifically addressing the major bottleneck for efficiently connecting optical fibres to silicon photonic (SiP) processors for use in telecom and data centres. An 84-channel fused silica interposer was introduced for high-density edge coupling of multicore fibres (MCFs) to a SiP chip. Femtosecond laser irradiation followed by chemical etching was further harnessed to open alignment sockets, permitting rapid assembly with precise locking of MCF positions for efficient coupling to laser written optical waveguides in the interposer. A 3D waveguide fanout design provided an attractive balancing of low losses, mode-matching, high channel density, compact footprint, and low crosstalk. The 3D additive and subtractive processes thus demonstrated the potential for higher scale integration and rapid photonic assembly and packaging of micro-optic components for telecom interconnects, with possible broader applications in integrated biophotonic chips or micro-displays.

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 score0.029
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
Bibliometrics0.0000.000
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 head0.013
GPT teacher head0.238
Teacher spread0.225 · 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