Molecular design and performance of emissive amide-containing compounds as corrosion inhibitors: synthesis, electrochemical evaluation, DFT calculations and molecular dynamics simulations
Bibliographic record
Abstract
IR and NMR spectroscopy confirmed their chemical structures. Electrochemical analyses, including open circuit potential and potentiodynamic polarization tests, showed that these compounds significantly reduce the corrosion rate of mild steel. They achieved inhibition efficiencies up to 80% at optimal concentrations. The enhanced performance of these inhibitors is linked to their greater molecular weight and longer alkyl chains, which improve adsorption and surface coverage. Photophysical investigations revealed notable solvatochromic effects and red shifts in polar solvents, indicating strong interactions with the environment. Density Functional Theory (DFT) calculations provided further insights into the molecular structure, electronic distributions, and adsorption behavior, confirming the higher efficiency of series naphthamide 6C-9C compared to benzamide 6C-9C. Moreover, molecular Dynamics (MD) simulations corroborated the formation of stable protective layers on the metal surface. From the DFT calculations it is evidently that naphthamide 9C exhibited a smaller HOMO-LUMO energy gap compared to compound benzamide 9C, indicating higher reactivity and greater inhibitory efficiency. The integration of experimental and theoretical findings confirms that amide-containing naphthalene and benzene derivatives are highly effective corrosion inhibitors, suitable for industrial applications.
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 | 0.000 | 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) | 0.000 | 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".