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Record W4309812920 · doi:10.1149/ma2022-02642348mtgabs

Corrosion Properties of Ni-P-B Dispersion Coating for Industrial Knives and Blades

2022· article· en· W4309812920 on OpenAlexaboutno aff
Nurul Amanina Binti Omar, Frank Koester, Frank Hahn, Andreas Bund

Bibliographic record

VenueECS Meeting Abstracts · 2022
Typearticle
Languageen
FieldEngineering
TopicMetal and Thin Film Mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsMetallurgyMaterials scienceTemperingCarbideCorrosionHigh-speed steelCoatingCeramicQuenching (fluorescence)Composite material

Abstract

fetched live from OpenAlex

Industrial blades, particularly the one used in food processing, requires not only a high hardness and a good wear protection but also an adequate corrosion protection. Currently, there is a wide variety of materials being used for this purpose that satisfy the above requirements. However, they come at a cost. Typically, steel with a high number of alloyed elements is chosen because the alloyed elements improved the steel quality. For example, incorporation of nickel, chromium, phosphorus and molybdenum in the steel improves amongst others the corrosion protection. However, the thermal processing of such steel, that is quenching, repeated tempering and followed by nitriding or boriding, is lengthy and complicated which drive the cost to produce knives using such steel up. Besides steel cutting tools, there is also cutting tools made from ceramic and carbide. Compared to steel knives, carbide knives have a longer lifespan and provide a higher temperature tolerance, which results in the application of the carbide cutting tools at higher speed and for longer periods without experiencing tool failure. Admittedly, due to carbides high hardness and thus the increase in difficulty to machine carbide, the production cost of carbide cutting tools is much higher compared to their steel counterparts. For ceramics, while the material is corrosion free and can maintain hardness and wear properties at a very high temperature, it is also more brittle than steel and carbide cutting tools. This results in premature chipping of the cutting edge and a shorter lifespan of the blade. To further reducing the production cost of industrial knives, the alternative of using a low alloyed steel which is coated with a hard coating and adjacently thermally treated for 1 h is investigated. This method is chosen because the tempering process of the low alloyed steel is not as lengthy as for high alloyed steel. The homogenously incorporated boron particles in the nickel phosphorus coating reduce the subsequent thermal treatment duration due to a shorter diffusion path compared to the conventional boriding. Previous study by the author [1] shows this approach to produce a high hardness at approx. 900 HV. Electroless nickel phosphorus coating is applied due to its good anti-corrosive properties. The presence of boron as particles in the coating or as boride after thermal treatment could change the corrosion behaviour of the coating. To date, no studies have yet been done to determine its corrosion properties and benchmarking this Ni-P-B dispersion coating with the other coating systems. In this study, the corrosion behaviour of the dispersion layer as coated and after thermal treatments at different temperatures is investigated. The corrosion resistance in NaCl 3.5 % is characterized though potentiodynamic polarisation and electrochemical impedance spectrometry. The results will be evaluated and compared to the other established coating systems. [1] The previous study will be presented at 241st ECS Meeting in Vancouver, Canada and has not yet been published at the time this abstract is submitted for the 242nd ECS Meeting in Atlanta.

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 score0.005
Threshold uncertainty score0.009

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)0.0020.001

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.

Opus teacher head0.036
GPT teacher head0.206
Teacher spread0.171 · 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
Published2022
Admission routes1
Has abstractyes

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