Retention Mechanisms of Citric Acid in Ternary Kaolinite-Fe(III)-Citrate Acid Systems Using Fe K-edge EXAFS and L3,2-edge XANES Spectroscopy
Bibliographic record
Abstract
Organic carbon (OC) stability in tropical soils is strongly interlinked with multivalent cation interaction and mineral association. Low molecular weight organic acids (LMWOAs) represent the readily biodegradable OC. Therefore, investigating retention mechanisms of LMWOAs in mineral-cation-LMWOAs systems is critical to understanding soil C cycling. Given the general acidic conditions and dominance of kaolinite in tropical soils, we investigated the retention mechanisms of citric acid (CA) in kaolinite-Fe(III)-CA systems with various Fe/CA molar ratios at pH ~3.5 using Fe K-edge EXAFS and L3,2-edge XANES techniques. With Fe/CA molar ratios >2, the formed ferrihydrite mainly contributed to CA retention through adsorption and/or coprecipitation. With Fe/CA molar ratios from 2 to 0.5, ternary complexation of CA to kaolinite via a five-coordinated Fe(III) bridge retained higher CA than ferrihydrite-induced adsorption and/or coprecipitation. With Fe/CA molar ratios ≤0.5, kaolinite-Fe(III)-citrate complexation preferentially occurred, but less CA was retained than via outer-sphere kaolinite-CA complexation. This study highlighted the significant impact of varied Fe/CA molar ratios on CA retention mechanisms in kaolinite-Fe(III)-CA systems under acidic conditions, and clearly showed the important contribution of Fe-bridged ternary complexation on CA retention. These findings will enhance our understanding of the dynamics of CA and other LMWOAs in tropical soils.
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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 | 0.000 |
| 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) | 0.001 | 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".