Ash Formation from Excluded Minerals Including Consideration of Mineral−Mineral Associations
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Bibliographic record
Abstract
During pulverized coal combustion processes, mineral matter in coals transforms into ash, which impacts combustion systems in various ways. According to its association with the coal matrix, mineral grains can be classified as included and excluded mineral grains. Excluded minerals behave differently from included minerals. In this paper, a state-of-the-art microscopic technique QEMSCAN was used to study the transformation of excluded minerals with a consideration of mineral−mineral associations. The concept of mineral−mineral association for excluded minerals refers to a single excluded mineral grain consisting of several different mineral phases. Three size-graded Australian coals have been burned in a laboratory drop-tube furnace at a temperature of 1400 °C. Ash particles are collected by a cyclone located at the outlet of a quench probe. Both mineral matter in coals and ash after combustion were analyzed by QEMSCAN. Transformation from mineral grain to ash particles resulted in changes in morphology, which has implications on ash fusion. Results show that illite as well as ankerite and siderite change sperical shape after combustion, while other minerals, including quartz, kaolinite, and calcite, do not have significant changes in shape. Mineral association of quartz with kaolinite has been positively identified in excluded minerals in coals and derived ash particles. However, mineral association of carbonates with silicates is not a common occurrence in the limited number of coals investigated.
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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 | 0.000 | 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