Interactions of Benzoic Acid and Phosphates with Iron Oxide Colloids Using Chemical Force Titration
Bibliographic record
Abstract
Colloidal iron oxides are an important component in soil systems and in water treatment processes. Humic-based organic compounds, containing both phenol and benzoate functional groups, are often present in these systems and compete strongly with phosphate species for binding sites on the iron oxide surfaces. Here, we examine the interaction of benzoate and phenolic groups with various iron oxide colloids using atomic force microscopy (AFM) chemical force titration measurements. Self-assembled monolayers (SAMs) of 4-(12-mercaptododecyloxy)benzoic acid and 4-(12-mercaptododecyloxy)phenol were used to prepare chemically modified Au-coated AFM tips, and these were used to probe the surface chemistry of a series of iron oxide colloids. The SAMs formed were also characterized using scanning tunneling microscopy, reflection-absorption infrared spectroscopy, and X-ray photoelectron spectroscopy. The surface pK(a) of 4-(12- mercaptododecyloxy)benzoic acid has been determined to be 4.0 +/- 0.5, and the interaction between the tip and the sample coated with a SAM of this species is dominated by hydrogen bonding. The chemical force titraton profile for an AFM probe coated with 4-(12- mercaptododecyloxy)benzoic acid and a bare iron oxide colloid demonstrates that the benzoic acid function group interacts with all three types of iron oxide sites present on the colloid surface over a wide pH range. Similar experiments were carried out on colloids precipitated in the presence of phosphoric, gallic, and tannic acids. The results are discussed in the context of the competitive binding interactions of solution species present in soils or in water treatment processes.
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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 | 0.001 | 0.001 |
| 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".