Mapping the Nanoscale Heterogeneity of Surface Hydrophobicity on the Sphalerite Mineral
Why this work is in the frame
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Bibliographic record
Abstract
Hydrophobic effect plays an important role in a wide range of natural phenomena and engineering applications, such as mineral froth flotation. In this work, atomic force microscope (AFM) force mapping was employed, for the first time, to probe the nanoscale heterogeneity of surface hydrophobicity and surface interactions on the sphalerite mineral surface before/after conditioning treatment (activated by copper sulfate and then treated by amyl xantahte). The AFM force mapping demonstrates that adhesion on sphalerite falls in a narrow range with a peak centered at 16.4 mN/m and adhesion on conditioned sphalerite falls in a wide range with a small peak centered at 15.5 mN/m and a large peak centered at 58.1 mN/m. It is evident that the sphalerite surface is hydrophilic with homogeneous surface hydrophobicity whereas conditioned sphalerite exhibits a heterogeneous distribution of surface hydrophobicity due to the nonuniform adsorption of xanthate. The significantly enhanced adhesion after conditioning treatment with chemical reagents originates from the additional hydrophobic attraction between the thiol-functionalized AFM tip and the hydrophobic domain on conditioned sphalerite. Fitted with the extended Derjaguin–Landau–Verwey–Overbeek (DLVO) theory by including the hydrophobic effect, the decay length of hydrophobic interaction on the hydrophobic domain was found to change from 0.7 to 1.2 nm depending on the adhesion region. The results provide insights into the fundamental understanding of nanoscale heterogeneity of surface hydrophobicity and the surface interaction mechanisms on different domains of solid mineral surfaces, and the methodology can be extended to many other heterogeneous surfaces and interfacial processes.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it