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Record W4414289658 · doi:10.18280/rcma.350420

A Study on the Use of Heterocyclic Compounds for Surface Protection in Acidic Environments

2025· article· fr· W4414289658 on OpenAlexvenueno aff
Asawer S. Temma, Hanan M. Ali

Bibliographic record

VenueRevue des composites et des matériaux avancés · 2025
Typearticle
Languagefr
FieldComputer Science
TopicEducational Robotics and Engineering
Canadian institutionsnot available
FundersUniversity of Basrah
KeywordsTafel equationAdsorptionPhysisorptionCorrosionCorrosion inhibitorHeteroatomMetalAlloyScanning electron microscope

Abstract

fetched live from OpenAlex

This study aims to assess the potential of two synthesized thiazolidine derivatives (AS3) and (AS4) in the capacity of preventing corrosion on N80 alloy steel in 1M hydrochloric acid medium.The electrochemical behavior, adsorption isotherms, activation energy, and surface morphology were analyzed using Tafel polarization curves, Langmuir adsorption model, Arrhenius equation, and scanning electron microscope (SEM) coupled with energy-dispersive spectroscopy (EDS) techniques.The findings indicate that both compounds function as efficient mixed-type inhibitors, with inhibition efficiency improving proportionally to inhibitor concentration but exhibiting a slight reduction at higher temperatures.This thermal sensitivity points to a predominant physisorption mechanism in the initial adsorption stages.SEM/EDS results confirmed the formation of a compact, protective surface film, validating the adsorption-driven protection mechanism.The significance of this study lies in the growing demand for environmentally safer and economically viable inhibitors for industrial applications involving acid-induced corrosion, especially in oil and gas applications where N80 carbon steel is widely used.Thiazolidine derivatives show strong affinity for steel surfaces, highlighting their suitability, due to their heteroatoms and π-electron system, offer promising coordination ability with metal surfaces.Thus, AS3 and AS4 represent valuable candidates for mitigating acid-induced corrosion, contributing to extended equipment life and reduced maintenance costs in aggressive environments.

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 head0.229
GPT teacher head0.320
Teacher spread0.091 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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