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Record W2897925219 · doi:10.2351/1.5062361

Development of non-planar interconnects for double-sided flexible copper substrates using laser assisted maskless microdeposition processes

2011· article· en· W2897925219 on OpenAlexaff
Steven Tong, Elahe Jabari, Hamidreza Alemohammad, Ehsan Toyserkani

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdditive Manufacturing and 3D Printing Technologies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMaterials sciencePlanarLaserDelamination (geology)Scanning electron microscopeElectronic packagingLayer (electronics)OptoelectronicsSelective laser sinteringNanotechnologyComposite materialOpticsComputer scienceSintering

Abstract

fetched live from OpenAlex

Non-planar (3D) interconnects have an important role in the electronic packaging industry today. They allow manufacturers to save materials and space when connecting circuit components on flexible and non-planar substrates. Nowadays, double-sided flexible substrates have attracted the electronic industry to develop miniaturized flexible devices, such as sensors-on-chips, effectively and compactly. This study reports on our preliminary results for the creation of non-planar silver interconnects on the edge of double-sided copper substrates separated by a layer of polyethylene terephthalate (PET) using laser-assisted maskless microdeposition (LAMM). In the LAMM process, which is a laser-based direct write technology, suspensions of silver nano-particles are used in a layer-by-layer deposition followed by laser post sintering. This study includes the characterization of the LAMM process to achieve desired conductivity in the produced interconnects, which is the main indicator of performance for the electronic packages. Several parameters, including the deposition and laser processing parameters, are optimized to achieve interconnects free of pores, cracks and delamination with reasonable bonding. For investigating the topography and microstructure of the interconnects, an optical microscope and scanning electron microscope (SEM) are used.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.000
Threshold uncertainty score0.001

Distilled classifier scores by category (both heads)

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 head0.075
GPT teacher head0.261
Teacher spread0.187 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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
Published2011
Admission routes1
Has abstractyes

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