Case study: alternatives to chromate conversion coatings for corrosion protection of zinc plated electronic shelves
Bibliographic record
Abstract
Hexavalent chromium oxide has been used for at least 60 years as a corrosion preventative for zinc and aluminum surfaces. This coating has been a very successful corrosion preventative for both painted and unpainted aluminum, zinc and other metal surfaces. In the electronics industry, chromate is used extensively to coat equipment shelves and other zinc plated steel and aluminum surfaces. Up to now, the electromagnetic interference shielding requirements of the electronic shelves were such that the contact and surface resistivity of the chromate coating provided no problem to EMI protection but now signal speed and proper amplitudes dictate that the coatings have higher electrical conductivity. The shelf is essentially a Faraday cage and the electronics within emanate a broad spectrum of EMI and in turn is sensitive to EMI, even between shelves. There is increasing pressure in the environmental and work safety agencies of the various governments to eliminate hexavalent chrome from processes and products because it is a toxic pollutant and uses a hazardous application process. Nortel became increasingly aware of the environmental and electrical issues for the use of hexavalent chrome and decided to search for alternatives in 1994. A program was initiated to explore conductive paints, zinc alloys and new conversion coatings to provide an alternative to the hexavalent chromate coating as a metal protectant and EMI shielding gasket interface.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".