Kinetics of phosphate adsorption on iron oxides formed under the influence of citrate
Bibliographic record
Abstract
The influence of organic acids on the formation of Fe oxyhydroxides and oxides has been intensively studied. However, scant attention has been paid to the subsequent effect on surface chemistry of the Fe oxides formed. The kinetics and mechanisms of phosphate adsorption by the Fe oxides formed in the presence of citrate ligands at initial citrate/Fe(II) molar ratios (MR) of 0, 0.001, 0.01, and 0.1 were investigated using the conventional batch method. The adsorption studies were conducted at the initial phosphate concentration of 0.5 mM and pH 4.0 during the reaction period from 2 min to 56 h at 278, 288, 298, and 313 K. The results show that the phosphate adsorption followed multiple second-order kinetics and had two distinct rates in each reaction system. The amount, rate coefficient, activation energy and pre-exponential factor of phosphate adsorption by the Fe oxides formed greatly varied with their structural and surface properties. These properties, which included crystal structure, specific surface area, surface porosity, surface geometry, and point of zero salt effect (PZSE), differed significantly with the initial citrate/Fe(II) MR at which Fe oxides were formed. The results of this study have cast the light on the role of organic acids such as citric acid in influencing the surface chemistry of naturally occurring Fe oxides through fundamental structural perturbation and the impact on the dynamics of phosphate in terrestrial and aquatic environments. Key words: Kinetics, activation energy, pre-exponential factor, phosphate, iron oxides, citric acid, structural perturbation
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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".