Comparative study on inhibitory performance of an ionic liquid on corrosion of 6061 Al‐10(vol.%) <scp>SiC</scp><sub>(P)</sub> composite material and base alloy
Bibliographic record
Abstract
Abstract Inhibitive performance of 1,3 dimethyl imidazolium dimethyl phosphate (DIDP) towards the corrosion of 6061‐Al (10 vol.%) SiC (P) composite (Al‐CM) and base alloy in 0.1 M HCl medium was studied using electrochemical impedance spectroscopy (EIS) and potentiodynamic polarization techniques at different temperatures. Optimization of inhibitor concentration was done to get maximum inhibition efficiency. Thermodynamic parameters were calculated by fitting the results into a suitable adsorption isotherm. Scanning electron microscope (SEM), energy‐dispersive X‐ray (EDX), and atomic force microscope (AFM) analyses were performed to understand surface morphology, elemental mapping, and surface roughness before and after the addition of DIDP. UV–visible and X‐ray diffraction (XRD) tests were performed to confirm the adsorption of inhibitor on the surfaces of materials. Studies revealed an increased rate of corrosion for Al‐CM than for the base alloy. The maximum inhibition efficiency for the base alloy was found to be 80.48% for the addition of 1000 ppm, and for Al‐CM, it was found to be 87.38% for the addition of 1400 ppm at 303 K. As the temperature increased, the inhibition efficiency decreased. The inhibitor was adsorbed physically on the surface of the metal by obeying the Freundlich adsorption isotherm. Surface studies confirmed the adsorption of DIDP on the surfaces of both Al‐CM and the base alloy.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".