Investigation of Mono/Competitive Adsorption of Environmentally Relevant Ionized Weak Acids on Graphite: Impact of Molecular Properties and Thermodynamics
Bibliographic record
Abstract
The thermodynamics of adsorption and competitive interactions of five weak acids on a graphite surface was assessed in alkaline solutions. Adsorption of the acids in mono- and multicompound solutions followed their Freundlich isotherms which suggest a diversity of graphite adsorption sites as confirmed by the presence of carboxylic and phenolic groups observed on graphite surfaces. Thermodynamic calculations assigned the formation of the negatively charged assisted hydrogen bond (-CAHB) between ionized solutes and adsorbent surface groups as the possible adsorption mechanism. However, the similar pKa values of current acids resulted in comparable free energies for -CAHB formation (ΔG(-CAHB)) being less than solvation free energies (ΔGSolv). Thus, additional ΔG is supplemented by increased hydrophobicity due to proton exchange of ionized acids with water (ΔΔG Hydrophobicity). Adsorption capacities and competition coefficients indicated that ΔΔG Hydrophobicity values depend on the neutral and ionized acid Kow. Competitive adsorption implies that multilayer adsorption may occur via hydrophobic bonding with the CH3 ends of the self-assembled layer which affects the acid adsorption capacities in mixtures as compared to monocompound solutions. The determination of adsorption mechanisms will assist in understanding of the fate and bioavailability of emerging and classical weak acids released into natural waters.
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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) | 0.000 | 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".