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Record W4391639977 · doi:10.1149/ma2023-02131133mtgabs

Electrochemical Deposition of N-Heterocyclic Carbene on Steels As a Corrosion Protective Layer

2023· article· en· W4391639977 on OpenAlexaff
T. Malsha Suduwella, Vikram Singh, Mark D. Aloisio, Ahmadreza Nezamzadeh, Cathleen M. Crudden, Janine Mauzeroll, Yuanjiao Li

Bibliographic record

VenueECS Meeting Abstracts · 2023
Typearticle
Languageen
FieldChemistry
TopicInorganic and Organometallic Chemistry
Canadian institutionsQueen's UniversityMcGill University
Fundersnot available
KeywordsElectrochemistryCorrosionLayer (electronics)CarbeneDeposition (geology)Materials scienceMetallurgyChemistryNanotechnologyElectrodeOrganic chemistryCatalysisGeologyPhysical chemistry

Abstract

fetched live from OpenAlex

Steels play a vital role in every aspect of day-to-day life. They are major components in construction, transportation, medicine, and etc. Despite their larger usability, steels are suffering from inevitable corrosion. Hence, finding a sustainable solution for corrosion has been a hot topic in the research field for centuries. One extensively studied strategy is applying a protective layer on top of metals. The recent findings show that N-heterocyclic carbene (NHC) has the potency to form a carbon-metal bond through self-assembling1 or electrochemical deposition2 on different metals such as Au, Pt, Pd, and Ag. Herein, we are trying to coat NHC on mild steel (MS) through electrochemical deposition to act as a corrosion protective layer. Deposition conditions will be optimized by varying the material concentrations, applied voltages, time durations, and substrate roughness. The NHC-coated surface is characterized by X-ray Photoelectron Spectroscopy (XPS), Matrix-Assisted Laser Desorption/Ionization (MALDI), and Atomic Force Microscope-Infrared Spectroscopy (AFM-IR). In addition, the contact angle measurements can be attributed to visualizing the differences in coatings under different conditions. The corrosion studies are utilized to understand the corrosion-resistant properties of the NHC coating. Moreover, the NHC moiety can be modified to perform better to inhibit corrosion and improve the properties of mild steel on their applications. Ultimately, this benchtop approach will be utilized and tested on a large scale and industrial level. (1) Crudden, C. M.; Horton, J. H.; Ebralidze, I. I.; Zenkina, O. V.; McLean, A. B.; Drevniok, B.; She, Z.; Kraatz, H.-B.; Mosey, N. J.; Seki, T. Ultra stable self-assembled monolayers of N-heterocyclic carbenes on gold. Nat. Chem. 2014, 6 (5), 409-414. (2) Amit, E.; Dery, L.; Dery, S.; Kim, S.; Roy, A.; Hu, Q.; Gutkin, V.; Eisenberg, H.; Stein, T.; Mandler, D. Electrochemical deposition of N-heterocyclic carbene monolayers on metal surfaces. Nat. Commun. 2020, 11 (1), 1-10.

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 score0.001
Threshold uncertainty score0.003

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)0.0010.000

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 head0.012
GPT teacher head0.240
Teacher spread0.228 · 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
Published2023
Admission routes1
Has abstractyes

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