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Record W2755474725 · doi:10.1002/cjce.23019

Corrosion‐resistant coating development with potential application in equipment of low‐temperature waste heat recovery

2017· article· en· W2755474725 on OpenAlexaffvenue
Quan Zhuang, Phil Geddis, Bruce Clements, Vivien Ko

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2017
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Optimization
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsMaterials scienceCorrosionCoatingInconelSlurryHeat exchangerMetallurgyComposite materialHeat transferFluoropolymerLayer (electronics)AlloyPolymer

Abstract

fetched live from OpenAlex

Abstract In order to improve corrosion resistance of a condensing heat exchanger, a fluoropolymer, perfluoroalkoxy alkane (PFA), fine powder in 30 wt% aqueous slurry was coated on metal coupons and a coating of high quality finish was obtained. The coating was characterized by microscopy and thickness measurements. The thickness of the coating can be controlled by the number of layers used for the application of wet spray. Hot acid bath corrosion tests showed that the coated coupon possesses the highest adhesion strength and excellent corrosion resistance (1.8–6.7 × 10 −3 mm/year), comparable to super alloys such as Inconel (1.1–26.2 × 10 −3 mm/year) and Hastelloy (0.3–19.8 × 10 −3 mm/year). A heat transfer coefficient analysis showed that across a heat transfer metal tube coated with PFA, the heat transfer resistance of the gas side film is one order of magnitude larger than the resistance from the coated layer. The developed coating could provide an alternative material solution for condensing heat exchangers used in low‐grade waste heat recovery.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.494
Threshold uncertainty score0.323

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 communication0.0000.000
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 head0.004
GPT teacher head0.168
Teacher spread0.164 · 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.

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

Citations8
Published2017
Admission routes2
Has abstractyes

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