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Record W4416883630 · doi:10.37665/ppjxvqa25605

C4NP: Lead-Free and Low Cost Solder Bumping Technology for Flip Chip and Wlcsp

2006· article· W4416883630 on OpenAlexaff
Klaus Ruhmer, Daniel Fleming, Peter Gruber

Bibliographic record

VenuePan Pacific Symposium · 2006
Typearticle
Language
FieldEngineering
TopicElectronic Packaging and Soldering Technologies
Canadian institutionsMicrosemi (Canada)
Fundersnot available
KeywordsBumpingSolderingFlip chipChip-scale packageWaferSolder paste

Abstract

fetched live from OpenAlex

ABSTRACT Today, various solder bumping technologies are being used in volume production. These include electroplating, solder paste printing, evaporation and the direct attach of preformed solder spheres. 1 However, all these established technologies have important limitations for fine pitch bumping with lead-free alloys: Evaporation is too costly in general, solder paste printing often does not provide the desired bump stand-off height when it comes to fine-pitch bumping, electroplating is found to be expensive and difficult to control for lead-free alloys and preformed solder spheres are only applicable for a pitch down to approximately 500 microns. These challenges in the transition to lead-free solder bumping has led the European Union to grant exemptions until 2010 from the ban of lead in certain solder bumping applications. However, the pressure to move to lead-free continues for the entire industry. C4NP (C4-New Process) is a novel solder bumping technology developed by IBM and commercialized by Suss MicroTec. C4NP addresses the limitations of existing bumping technologies by enabling low-cost, fine pitch bumping using a variety of lead-free solder alloys. C4NP is a solder transfer technology where molten solder is injected into pre-fabricated and reusable glass templates (molds). Mold and wafer are brought into close proximity and solder bumps are transferred onto the entire 300mm (or smaller) wafer in a single process step. C4NP technology is capable of fine pitch bumping while offering the same alloy selection flexibility as solder paste printing. The simplicity of the C4NP process makes it a low cost solution for both, fine-pitch FC in package as well as WLCSP bumping applications. This paper reviews the current status of the first C4NP lines installed at semiconductor manufacturers. It discusses the relevant process equipment technology and a manufacturing cost model. Last but not least, the presentation includes manufacturing data provided by IBM’s packaging operation at the Hudson Valley Research Park in East Fishkill, NY.

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)0.000
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 score0.231
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.007
GPT teacher head0.205
Teacher spread0.198 · 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 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
Published2006
Admission routes1
Has abstractyes

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