MétaCan
Menu
Back to cohort
Record W2912161254 · doi:10.1016/j.jksus.2019.01.013

Corrosion inhibition of mild steel in 1 M HCl by sweet melon peel extract

2019· article· en· W2912161254 on OpenAlex

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 King Saud University - Science · 2019
Typearticle
Languageen
FieldMaterials Science
TopicCorrosion Behavior and Inhibition
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsTafel equationCorrosionChemistryElectrolyteActivation energyMetalNuclear chemistryMelonDissolutionMetallurgyElectrochemistryMaterials scienceElectrodeOrganic chemistry

Abstract

fetched live from OpenAlex

Corrosion inhibition of mild steel by sweet melon (Cucumis melo L) peel (SM) extract in 1 M HCl solution was evaluated by weight loss and potentiodynamic polarization methods. Various SM extracts concentrations such as 0.05, 0.1, 0.2, 0.3, 0.4, and 0.5 g/l were added and corrosion rate (CR) of mild steel and inhibition efficiency (IE) were determined at various temperatures from 295 to 333 K. The appreciable decrease in CR with increase in SM extract concentration was observed at each temperature. However, the typically accelerated CR at each SM extract with the rise in temperature corresponded to the increased kinetic activities at the metal/electrolyte interface. By the addition of 0.5 g/l SM extract, ∼5 times lower CR of mild steel at high temperature (333 K) than in blank acidic solution confirmed its strong inhibitive efficacy. The relatively large variation in the anodic Tafel slope and progressive decrease in CR with an increase in the SM extract concentration validated the restricted dissolution of mild steel. The barrier characteristics of the SM extract layer and its chemical interaction with the surface was evaluated from the low activation energy (Ea) values that fluctuated from ∼20 to 23 kJ/mole. The increase in kad increased from 0.602 to 1.053 (g/l)−1 and decrease in ΔG°ad (−3.74 to −4.91 kJ/mole) with an increase in temperature from 295 to 333 K assured the spontaneous interaction of SM extract molecules with the steel surface.

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 score0.027
Threshold uncertainty score0.371

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.014
GPT teacher head0.238
Teacher spread0.224 · 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