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Record W3200721683 · doi:10.1016/j.arabjc.2021.103445

Microbiologically-influenced corrosion of the electroless-deposited NiP-TiNi – Coating

2021· article· en· W3200721683 on OpenAlexaff
Eman M. Fayyad, P. Abdul Rasheed, Noora Al‐Qahtani, Aboubakr M. Abdullah, Fatma Hamdy, M. A. Sharaf, Mohammad K. Hassan, Khaled A. Mahmoud, A.M.A. Mohamed, George Jarjoura, Zoheir Farhat

Bibliographic record

VenueArabian Journal of Chemistry · 2021
Typearticle
Languageen
FieldMaterials Science
TopicCorrosion Behavior and Inhibition
Canadian institutionsDalhousie University
FundersQatar National Research FundQatar UniversityQatar Foundation
KeywordsDielectric spectroscopyNIPCoatingX-ray photoelectron spectroscopyCorrosionChemistryScanning electron microscopeNanocompositeMetallurgyCarbon steelEnergy-dispersive X-ray spectroscopyChemical engineeringSeawaterMaterials scienceComposite materialElectrochemistryElectrodeOrganic chemistry

Abstract

fetched live from OpenAlex

In this study, we reveal the microbiologically influenced corrosion (MIC) behavior of the new electroless NiP-TiNi nanocomposite coating in simulated seawater using the electrochemical impedance spectroscopy (EIS) technique after different periods of incubation time (7, 10, 14, 21, 28 days) in a sulfate-reducing bacteria (SRB) medium. The biofilm formation and the corrosion products were characterized using the scanning electron microscope (SEM) and X-ray photoelectron spectroscopy (XPS). The EIS results revealed the carbon steel (CS)/NiP-TiNi and NiP-TiNi/SRB biofilm interfaces' characteristics after different incubation times in the SRB media. EIS measurements revealed that the NiP-TiNi nanocomposite coating's MIC resistances are superior relative to API X80 carbon steel and a TiNi-free NiP coating, with ∼93% of corrosion inhibition efficiency after 28 days of incubation.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.550

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)0.0010.000

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 head0.009
GPT teacher head0.230
Teacher spread0.221 · 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

Citations18
Published2021
Admission routes1
Has abstractyes

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