MétaCan
Menu
Back to cohort
Record W4409157125 · doi:10.1080/00084433.2025.2484036

An overview of corrosion and its control by the surfactants: a mini-review

2025· article· en· W4409157125 on OpenAlexaff
Smitha Shree Subramaniyam, Srilatha Rao, Padmalatha Rao, Sali Mouhamadou, Prashanth Gopala Krishna, K. Asha

Bibliographic record

VenueCanadian Metallurgical Quarterly · 2025
Typearticle
Languageen
FieldMaterials Science
TopicCorrosion Behavior and Inhibition
Canadian institutionsHorizon College and Seminary
Fundersnot available
KeywordsCorrosionBiochemical engineeringEnvironmental scienceMaterials scienceProcess engineeringMetallurgyChemical engineeringEngineering

Abstract

fetched live from OpenAlex

In recent years, studies of the effectiveness of various surfactant inhibitors in inhibiting corrosion have been published. In acid media, surfactants have generally demonstrated inhibitory efficiency (IE%) ranging from roughly 60% to over 98%. The literature on the cationic, anionic, zwitter ionic, neutral, and Gemini surfactants used to prevent steel corrosion in a range of acidic environments is compiled in this review. Also, the relationship between the amphiphilic nature of surfactants and a lower corrosion rate when using various surfactant classes. The surfactant structures, corrosion rates (CR), free energy of adsorption (ΔG°ads), and acid medium-dependent inhibition efficiencies (IE%) are highlighted. By indicating the connection between surfactants’ molecular structure and adsorption mechanisms, the study presents the most reliable quantitative evaluation of surfactants’ effectiveness as corrosion inhibitors in a range of environmental media. The fact that the majority of inhibitors followed Langmuir adsorption isotherm suggested a systematic adsorption mechanism.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.816
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0020.000

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 head0.025
GPT teacher head0.298
Teacher spread0.273 · 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.

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

Citations4
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Metallurgical QuarterlySame topicCorrosion Behavior and InhibitionFrench-language works237,207