Understanding the Deposition and Surface Interactions of Gypsum
Bibliographic record
Abstract
Using a surface forces apparatus (SFA) and an atomic force microscope (AFM), we have studied the deposition of gypsum on a silicate mineral (mica) and their surface interactions. An exponential force–distance repulsion relation was obtained for two rough (gypsum) crystal surfaces with root-mean-square (rms) roughness between 4 and 200 nm on approach and separation after the initial contact. The effective surface energies were estimated as γ eff = 32.8 and 7 mJ/m 2 for gypsum surfaces with an rms roughness of ∼8 and ∼100 nm, respectively, which increase with a decrease of the rms roughness, approaching the thermodynamic value ∼48 mJ/m 2 estimated by a three-probe-liquid contact angle measurement. The repulsive force observed for rough gypsum surfaces was found to be a mainly elastic force due to asperity interactions. The surface forces measured between two silicate mineral surfaces (mica) in CaSO 4 solutions were fitted well by the Derjaguin–Landau–Verwey–Overbeek (DLVO) theory at low concentrations (10 –4 –10 –2 M) but deviated at higher concentration. Our results have provided insight into the basic surface interaction mechanisms of gypsum and silicates in many mineral flotation processes and industrial operations.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".