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Record W2883240268 · doi:10.1080/16583655.2018.1500514

Experimental and computational chemistry studies on the inhibition of aluminium and mild steel in 0.1 M HCl by 3-nitrobenzoic acid

2018· article· en· W2883240268 on OpenAlex
N. Eddy, Paul Ocheje Ameh, Nsikak B. Essien

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Taibah University for Science · 2018
Typearticle
Languageen
FieldMaterials Science
TopicCorrosion Behavior and Inhibition
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsAdsorptionChemistryEndothermic processCorrosionAluminiumEnthalpyMetalLangmuir adsorption modelCorrosion inhibitorInorganic chemistryPolarization (electrochemistry)Nuclear chemistryPhysical chemistryOrganic chemistryThermodynamics

Abstract

fetched live from OpenAlex

The effectiveness of 3-nitrobenzoic acid towards the inhibition of the corrosion of mild steel and aluminium in solution of HCl was investigated using theoretical and experimental methods (weight loss, thermometric, polarization, FTIR and SEM techniques). Inhibition efficiency of 3-nitrobenzoic acid, evaluated from weight loss technique ranged from 71% to 90% and from 71% to 82% for mild steel and aluminium, respectively. Results from linear polarization and potentiodynamic studies were comparable to weight loss results. Calculated kinetic (activation energy), thermodynamic (changes in entropy and enthalpy) and adsorption parameters indicated that the adsorption of the inhibitor on the surface of the respective metal is accompanied by molecular association and is endothermic, spontaneous and favoured the mechanism of physical adsorption. Best-fitted adsorption isotherms were Langmuir and Frumkin models, which gave evidences for the existence of interaction, characterized by attractive behaviour of the inhibitor on both mild steel and aluminium surfaces. Scanning electron micrographs of the metal before and after inhibition clearly revealed that the inhibitor prevented crevice and pitting corrosion by forming adsorbed protective layer on the respective metal surface. FTIR spectra of the inhibitor and the corrosion products indicated the formation of new bond, existence of interaction between the inhibitor molecules and the involvement of some functional groups in the adsorption and inhibition processes. Quantum chemical study revealed that the inhibitor is adsorbed on the metal surface through the nitro functional group in the ring. Calculated semi empirical parameters were comparable to those reported for excellent corrosion inhibitors.

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.

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 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 score0.007
Threshold uncertainty score0.332

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.028
GPT teacher head0.278
Teacher spread0.251 · 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