Anticorrosive Effects of Essential Oils Obtained from White Wormwood and Arâr Plants
Bibliographic record
Abstract
This article is part of the contribution to the development of two medicinal plants widely used by the Moroccan population: white wormwood (Artemisia herba-alba) andArâr (Juniperus phoenicea), species belonging to the Asteraceae and Cupressaceae families, respectively. The present work was conducted to investigate the chemical composition and anticorrosive properties of essential oils (EOs) extracted from these plants. The chemical analysis of the essential oils (EOs) was carried out by GC-MS/MS. Potentiodynamic polarization, electrochemical impedance spectroscopy (EIS), and quantum chemical calculations by density-functional theory at B3lYP were used to study the anticorrosive effect of the researched oils on mild steel in 1 M hydrochloric acid solution. Moreover, SEM-EDX analysis was used to identify the surface morphology of mild steel surface. GC-MSMS results showed the presence of 32 potentially active compounds in the EOs of Artemisia herba-alba. The average yield of the EOs was about 1.39 ± 0.17 mL/100 g dry matter. Beta thujone (30.07%) and alpha thujone (13.32%) are the main components, while for the EOs of Juniperus phoenicea, the study showed the presence of 30 constituents, with alpha-pinene (43.61%) and manoyl oxide (11.5%) as the main components. The average yield of HE was 1.10 ± 0.03 mL/100 g dry matter. The findings demonstrated an important anticorrosive action of EOs from Artemisia herba-alba and Juniperus phoenicea. Notably, the experimental results showed good efficiency of the studied essential oils and correlated well with the density-functional theory (DFT) calculations. The results of potentiodynamic polarization measurements showed that hydrazone acted as a mixed-type inhibitor. The EIS results showed an increase in charge transfer resistance accompanied by a noticeable decrease in Cdl values, revealing that both studied oils were effective as reliable inhibitors for the protection of mild steel in 1 M HCl solution. Also, the efficiency decreased with decreasing inhibitor concentrations. Surface studies ensure the effectiveness of both investigated oils and the reduction of the surface roughness of mild steel. Furthermore, DFT results of the major constituents of Artemisia herba-alba and Juniperus phoenicea EOs revealed insights into the chemical reactivity of the tested oils while supporting the experimental conclusions and showed outstanding adsorption ability of both investigated EOs on the steel surface.
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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".