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Corrosion Inhibition Study Using Ofloxacin (Antibiotics) As Corrosion Inhibitor for Mild Steel in Hci Medium

2025· article· W7117327900 on OpenAlexaff
Tijjani Ahmad Hakeem

Bibliographic record

VenueInternational Journal of Research and Innovation in Applied Science · 2025
Typearticle
Language
FieldMaterials Science
TopicCorrosion Behavior and Inhibition
Canadian institutionsDepartment of National Defence
Fundersnot available
KeywordsOfloxacinHydrochloric acidCorrosionAdsorptionCorrosion inhibitorGravimetric analysis

Abstract

fetched live from OpenAlex

This study explores the corrosion inhibition performance of ofloxacin for mild steel in 0.1 M and 0.5 M hydrochloric acid solutions and was investigated using the gravimetric (weight loss) method at 298 K. Different concentrations of ofloxacin (0.1–0.5 g/L) were employed to evaluate its effect on corrosion rate, inhibition efficiency and surface coverage. The results revealed that ofloxacin significantly reduced the corrosion rate of mild steel in both acidic media. Maximum inhibition efficiencies of 78.86% in 0.5 M HCl and 70.86% in 0.1 M HCl were achieved at 0.5 g/L inhibitor concentration. The inhibition efficiency increased with increasing inhibitor concentration, indicating adsorption-controlled inhibition. Adsorption of ofloxacin on the mild steel surface followed the Langmuir adsorption isotherm, suggesting monolayer adsorption. The study confirms that ofloxacin is an effective corrosion inhibitor for mild steel in hydrochloric acid 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 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)0.017
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.015
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0110.009
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0000.001
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 head0.086
GPT teacher head0.437
Teacher spread0.351 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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