Theoretical investigation for the designing of novel antioxidants
Bibliographic record
Abstract
In this study, the antioxidant potential of salicylic acid and its derivatives was determined. O–H bond dissociation enthalpy ionization potential and spin densities were computed, which are important characteristics of antioxidants. We have designed new antioxidants on the basis of information obtained from the results of this study and a literature review. O–H bond dissociation enthalpy, ionization potential, and spin densities of designed compounds were also calculated to analyze the effect of the size of the heterocyclic ring, the electronegativity of the heteroatom, the number of hydroxyl groups, and intramolecular hydrogen bonding. The results reveal that compounds with a larger heterocyclic ring, fewer electronegative atoms, and greater number of hydroxyl groups have enhanced antioxidant activity. A comparison of bond dissociation enthalpy of designed compounds IIIA and IV with that of phenolic acid antioxidants shows that these designed compounds are potent antioxidants. From statistical analysis, it is found that for designed compounds, good correlation was found between spin density and bond dissociation enthalpy. The present theoretical investigation will provide help to understand the biological activity of salicylic acid and its derivatives for better utilization in the fields of pharmacy and the food industry. New antioxidants with better antioxidant activity can be synthesized on the basis of the results of this study.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".