Wettability and floatability of coal macerals as derived from flotations in methanol solutions
Bibliographic record
Abstract
In this study wettability and floatability of coal petrographic components were examined using the concept of critical surface tension. Two techniques were studied; film flotation and small-scale flotation tests. Both tests use Zisman’s concept of critical surface tension of solids. In these tests particles are separated according to their respective critical surface tension of wettability (film flotation) or critical surface tension of floatability (small-scale flotation). Surface heterogeneity of coal particles arises from the chemical composition of coal surface. The coal macerals are known to have different chemical composition and surface properties. Surface properties of macerals and their flotation response have usually been evaluated with the contact angle or direct flotation tests. In this study, the estimation of surface properties of coal macerals was accomplished by studying their critical surface tension of wettability and floatability. The wettability distributions of coal samples of various petrographic composition were obtained from film flotation. Wettability of petrographic components was evaluated in terms of an average critical surface tension of wettability. In small-scale flotation experiments, coal particles were separated according to their critical surface tension of floatability. Differences in floatability and wettability distributions of coal lithotypes and maceral concentrates are discussed. Microscopic examination of the products from film and small-scale flotations was used to further study the effect of coal petrographic composition on the wettability and floatability.
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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".