Chemical and Electrochemical Studies on Expired Lioresal Drugs as Corrosion Inhibitors for Carbon Steel in Sulfuric Acid
Bibliographic record
Abstract
Lioresal is a muscle relaxer and an antispasmodic agent, known as Lioresal. The active ingredient is β-(Aminomethyl)-p-chlorohydrocinnamic acid, a racemic mixture of the R,(-) and S, (+) isomers. It affects directly the spinal cord with adverse effects including drowsiness, dizziness, weakness, fatigue, headache, trouble sleeping, nausea and vomiting, urinary retention, or constipation. Therefore, the accumulation of expired or unused Lioresal in our home is so dangerous and harmful for our children. The present work introduces an idea for using expired Lioresal as a corrosion inhibitor for steel in 1.0 M H2SO4. The effect of both concentration and temperature were studied. The inhibition efficiency was found to increase with concentration and decreased with rising temperature. Chemical, electrochemical, and analytical techniques, namely, gravimetric, thermometric, gasometric, acidimetric, AAS, and potentiodynamic polarization were used to evaluate the inhibition action of the expired Lioresal drugs. The inhibition performance is due to the adsorption and adhesion of drugs constituent molecules on the steel surface. The adsorption was found to obey Langmuir isotherm. The surface area available for the anodic dissolution of iron and cathodic hydrogen evolution process diminishes without changing the reaction mechanism. The values of Ecorr. readings slowly decrease to negative values, showing that these inhibitors are mixed-type inhibitors mainly cathodic inhibitors. The data obtained from different techniques are in good agreement with each other. Electrochemical and analytical Techniques are efficient and accurate in the determination of the corrosion rate and inhibition performance of expired drugs in an aqueous medium.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".