Analyses on Forms of Sulfurin Chinese Yanzhou Coal and Their Transformation during Pyrolysis by X-ray Absorption Spectroscopy
Bibliographic record
Abstract
In the processof pyrolysis, inherent and the added minerals are the main factors to affectthe transformation and distribution of sulfur in coal. In order to cleanly and efficiently use the inferior coal with high-sulfur content, Yanzhou coal containing 5wt % sulfur was chosen as the sample to do pyrolysis experiments in a fixed-bed reactor. The effect of iron additive on the sulfur forms and their transformation during coal pyrolysis wasstudied in this paper. Fe and S forms in raw coal with (FC) and without (RC) iron additive and their chars from different temperature were determined by XANES, and the gaseous products and total sulfur in char were also considered. The results show that addition of Fe in coal can make more sulfur retained in the char. The transformation of sulfur exists in the entire coal pyrolysis process from 200 to 1000 °C, and more inorganic sulfur was produced during the FC pyrolysis at high temperature (700–1000 °C). FeS existing in the FC char from 1000°C occupies about 62% of the total sulfur in char, but there is almost no FeS in the RC char at 1000 °C. The semi-quantitative analysis of XANES data by LCF fitting will also be discussed.
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How this classification was reachedexpand
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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".