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Record W4416884148 · doi:10.37665/hazblcz89064

The Remarkable Return of Post-Reflow Cleaning as a Mainstream Process to Improve Reliability

2023· article· W4416884148 on OpenAlexaboutno aff

Bibliographic record

VenueHarsh Environments Conference · 2023
Typearticle
Language
FieldMaterials Science
TopicPolymer Science and PVC
Canadian institutionsnot available
Fundersnot available
KeywordsMainstreamMontreal ProtocolProcess (computing)Reliability (semiconductor)Order (exchange)Work (physics)Subject (documents)Treaty

Abstract

fetched live from OpenAlex

ABSTRACT Today, in modern times, society values cleanliness. The pandemic exaggerated the degree to which we desire, expect, and even demand cleanliness. Even in “normal times”, cleanliness is revered. We wash our bodies, dishes, cars, and pets. We expect cleanliness in our hotels and restaurants. We require cleanliness, to the point of sterility, in our operating rooms. In many public restrooms, we even hire people to inspect for cleanliness and publish inspection reports. Cleanliness has become a normal part of life, except in one aspect of our life. Part of our life that ensures our safety, prepares our food, transports us to work and play, monitors our health, and so much more. I'm referring to electronics. Once regarded as vital, the level of importance of a clean circuit assembly has been demoted. How did the cleanliness of circuit assemblies, once required, get shoved aside? There's one simple answer; the environment. During the 1980's, scientists discovered a “hole” in the Earth's ozone layer and attributed it to, among other things, chlorofluorocarbons (CFC's). In order to protect the ozone layer, or at least slow down the shrink-rate, a treaty was signed, referred to as the Montreal Protocol [figure 1], originally by eleven countries, that would phase out production, and consequently availability, of most CFC-based solvents within a ten-year time frame. That was 1989. By law, these CFC-based solvents would be no longer produced by 1999. The wildly popular cleaning/defluxing chemicals of the day were largely CFC-based and therefore subject to the ban. Necessity being the mother of invention, a new flux was introduced promising to leave behind an invisible and benign residue, not harmful to circuit assemblies. This new “noclean” flux would eliminate the cleaning requirement. Almost instantly, the electronic assembly industry switched to no-clean fluxes and abandoned their cleaning processes. While some high-reliability manufacturers such as military and medical maintained their cleaning processes, the majority of the industry exchanged their cleaning systems and processes for the promise of a “clean without cleaning” circuit assembly.

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)0.013
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.016
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.005
Scholarly communication0.0050.007
Open science0.0020.003
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0160.007

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 head0.015
GPT teacher head0.262
Teacher spread0.247 · 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 designNot applicable
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
Published2023
Admission routes1
Has abstractyes

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